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The Impact of Social Media: Is it Irreplaceable?

July 26, 2019 • 15 min read.

Social media as we know it has barely reached its 20th birthday, but it’s changed the fabric of everyday life. What does the future hold for the sector and the players currently at the top?

• Public Policy

In little more than a decade, the impact of social media has gone from being an entertaining extra to a fully integrated part of nearly every aspect of daily life for many.

Recently in the realm of commerce, Facebook faced skepticism in its testimony to the Senate Banking Committee on Libra, its proposed cryptocurrency and alternative financial system . In politics, heartthrob Justin Bieber tweeted the President of the United States, imploring him to “let those kids out of cages.” In law enforcement, the Philadelphia police department moved to terminate more than a dozen police officers after their racist comments on social media were revealed.

And in the ultimate meshing of the digital and physical worlds, Elon Musk raised the specter of essentially removing the space between social and media through the invention — at some future time — of a brain implant that connects human tissue to computer chips.

All this, in the span of about a week.

As quickly as social media has insinuated itself into politics, the workplace, home life, and elsewhere, it continues to evolve at lightning speed, making it tricky to predict which way it will morph next. It’s hard to recall now, but SixDegrees.com, Friendster, and Makeoutclub.com were each once the next big thing, while one survivor has continued to grow in astonishing ways. In 2006, Facebook had 7.3 million registered users and reportedly turned down a $750 million buyout offer. In the first quarter of 2019, the company could claim 2.38 billion active users, with a market capitalization hovering around half a trillion dollars.

“In 2007 I argued that Facebook might not be around in 15 years. I’m clearly wrong, but it is interesting to see how things have changed,” says Jonah Berger, Wharton marketing professor and author of Contagious: Why Things Catch On . The challenge going forward is not just having the best features, but staying relevant, he says. “Social media isn’t a utility. It’s not like power or water where all people care about is whether it works. Young people care about what using one platform or another says about them. It’s not cool to use the same site as your parents and grandparents, so they’re always looking for the hot new thing.”

Just a dozen years ago, everyone was talking about a different set of social networking services, “and I don’t think anyone quite expected Facebook to become so huge and so dominant,” says Kevin Werbach, Wharton professor of legal studies and business ethics. “At that point, this was an interesting discussion about tech start-ups.

“Today, Facebook is one of the most valuable companies on earth and front and center in a whole range of public policy debates, so the scope of issues we’re thinking about with social media are broader than then,” Werbach adds.

Cambridge Analytica , the impact of social media on the last presidential election and other issues may have eroded public trust, Werbach said, but “social media has become really fundamental to the way that billions of people get information about the world and connect with each other, which raises the stakes enormously.”

Just Say No

“Facebook is dangerous,” said Sen. Sherrod Brown (D-Ohio) at July’s hearing of the Senate Banking Committee. “Facebook has said, ‘just trust us.’ And every time Americans trust you, they seem to get burned.”

Social media has plenty of detractors, but by and large, do Americans agree with Brown’s sentiment? In 2018, 42% of those surveyed in a Pew Research Center survey said they had taken a break from checking the platform for a period of several weeks or more, while 26% said they had deleted the Facebook app from their cellphone.

A year later, though, despite the reputational beating social media had taken, the 2019 iteration of the same Pew survey found social media use unchanged from 2018.

Facebook has its critics, says Wharton marketing professor Pinar Yildirim, and they are mainly concerned about two things: mishandling consumer data and poorly managing access to it by third-party providers; and the level of disinformation spreading on Facebook.

“Social media isn’t a utility. It’s not like power or water where all people care about is whether it works. Young people care about what using one platform or another says about them.” –Jonah Berger

“The question is, are we at a point where the social media organizations and their activities should be regulated for the benefit of the consumer? I do not think more regulation will necessarily help, but certainly this is what is on the table,” says Yildirim. “In the period leading to the [2020 U.S. presidential] elections, we will hear a range of discussions about regulation on the tech industry.”

Some proposals relate to stricter regulation on collection and use of consumer data, Yildirim adds, noting that the European Union already moved to stricter regulations last year by adopting the General Data Protection Regulation (GDPR) . “A number of companies in the U.S. and around the world adopted the GDPR protocol for all of their customers, not just for the residents of EU,” she says. “We will likely hear more discussions on regulation of such data, and we will likely see stricter regulation of this data.”

The other discussion bound to intensify is around the separation of Big Tech into smaller, easier to regulate units. “Most of us academics do not think that dividing organizations into smaller units is sufficient to improve their compliance with regulation. It also does not necessarily mean they will be less competitive,” says Yildirim. “For instance, in the discussion of Facebook, it is not even clear yet how breaking up the company would work, given that it does not have very clear boundaries between different business units.”

Even if such regulations never come to pass, the discussions “may nevertheless hurt Big Tech financially, given that most companies are publicly traded and it adds to the uncertainty,” Yildirim notes.

One prominent commentator about the negative impact of social media is Jaron Lanier, whose fervent opposition makes itself apparent in the plainspoken title of his 2018 book Ten Arguments for Deleting Your Social Media Accounts Right Now . He cites loss of free will, social media’s erosion of the truth and destruction of empathy, its tendency to make people unhappy, and the way in which it is “making politics impossible.” The title of the last chapter: “Social Media Hates Your Soul.”

Lanier is no tech troglodyte. A polymath who bridges the digital and analog realms, he is a musician and writer, has worked as a scientist for Microsoft, and was co-founder of pioneering virtual reality company VPL Research. The nastiness that online existence brings out in users “turned out to be like crude oil for the social media companies and other behavior manipulation empires that quickly came to dominate the internet, because it fuelled negative behavioral feedback,” he writes.

“Social media has become really fundamental to the way that billions of people get information about the world and connect with each other, which raises the stakes enormously.” –Kevin Werbach

Worse, there is an addictive quality to social media, and that is a big issue, says Berger. “Social media is like a drug, but what makes it particularly addictive is that it is adaptive. It adjusts based on your preferences and behaviors,” he says, “which makes it both more useful and engaging and interesting, and more addictive.”

The effect of that drug on mental health is only beginning to be examined, but a recent University of Pennsylvania study makes the case that limiting use of social media can be a good thing. Researchers looked at a group of 143 Penn undergraduates, using baseline monitoring and randomly assigning each to either a group limiting Facebook, Instagram, and Snapchat use to 10 minutes per platform per day, or to one told to use social media as usual for three weeks. The results, published in the Journal of Social and Clinical Psychology , showed significant reductions in loneliness and depression over three weeks in the group limiting use compared to the control group.

However, “both groups showed significant decreases in anxiety and fear of missing out over baseline, suggesting a benefit of increased self-monitoring,” wrote the authors of “ No More FOMO: Limiting Social Media Decreases Loneliness and Depression .”

Monetizing a League (and a Reality) All Their Own

No one, though, is predicting that social media is a fad that will pass like its analog antecedent of the 1970s, citizens band radio. It will, however, evolve. The idea of social media as just a way to reconnect with high school friends seems quaint now. The impact of social media today is a big tent, including not only networks like Facebook, but also forums like Reddit and video-sharing platforms.

“The question is, are we at a point where the social media organizations and their activities should be regulated for the benefit of the consumer?” –Pinar Yildirim

Virtual worlds and gaming have become a major part of the sector, too. Wharton marketing professor Peter Fader says gamers are creating their own user-generated content through virtual worlds — and the revenue to go with it. He points to one group of gamers that use Grand Theft Auto as a kind of stage or departure point “to have their own virtual show.” In NoPixel, the Grand Theft Auto roleplaying server, “not much really happens and millions are tuning in to watch them. Just watching, not even participating, and it’s either live-streamed or recorded. And people are making donations to support this thing. The gamers are making hundreds of thousands of dollars.

“Now imagine having a 30-person reality show all filmed live and you can take the perspective of one person and then watch it again from another person’s perspective,” he continues. “Along the way, they can have a tip jar or talk about things they endorse. That kind of immersive media starts to build the bridge to what we like to get out of TV, but even better. Those things are on the periphery right now, but I think they are going to take over.”

Big players have noticed the potential of virtual sports and are getting into the act. In a striking example of the physical world imitating the digital one, media companies are putting up real-life stadiums where teams compete in video games. Comcast Spectator in March announced that it is building a new $50 million stadium in South Philadelphia that will be the home of the Philadelphia Fusion, the city’s e-sports team in the Overwatch League.

E-sports is serious business, with revenues globally — including advertising, sponsorships, and media rights — expected to reach $1.1 billion in 2019, according to gaming industry analytics company Newzoo.

“E-sports is absolutely here to stay,” says Fader, “and I think it’s a safe bet to say that e-sports will dominate most traditional sports, managing far more revenue and having more impact on our consciousness than baseball.”

It’s no surprise, then, that Facebook has begun making deals to carry e-sports content. In fact, it is diversification like this that may keep Facebook from ending up like its failed upstart peers. One thing that Facebook has managed to do that MySpace, Friendster, and others didn’t, is “a very good job of creating functional integration with the value they are delivering, as opposed to being a place to just share photos or send messages, it serves a lot of diversified functions,” says Keith E. Niedermeier, director of Wharton’s undergraduate marketing program and an adjunct professor of marketing. “They are creating groups and group connections, but you see them moving into lots of other services like streaming entertainment, mobile payments, and customer-to-customer buying and selling.”

“[WeChat] has really instantiated itself as a day-to-day tool in China, and it’s clear to me that Facebook would like to emulate that sort of thing.” –Keith Niedermeier

In China, WeChat has become the biggest mobile payment platform in the world and it is the platform for many third-party apps for things like bike sharing and ordering airplane tickets. “It has really instantiated itself as a day-to-day tool in China, and it’s clear to me that Facebook would like to emulate that sort of thing,” says Niedermeier.

Among nascent social media platforms that are particularly promising right now, Yildirim says that “social media platforms which are directed at achieving some objectives with smaller scale and more homogenous people stand a higher chance of entering the market and being able to compete with large, general-purpose platforms such as Facebook and Twitter.”

Irreplaceable – and Damaging?

Of course, many have begun to believe that the biggest challenge around the impact of social media may be the way it is changing society. The “attention-grabbing algorithms underlying social media … propel authoritarian practices that aim to sow confusion, ignorance, prejudice, and chaos, thereby facilitating manipulation and undermining accountability,” writes University of Toronto political science professor Ronald Deibert in a January essay in the Journal of Democracy .

Berger notes that any piece of information can now get attention, whether it is true or false. This means more potential for movements both welcome as well as malevolent. “Before, only media companies had reach, so it was harder for false information to spread. It could happen, but it was slow. Now anyone can share anything, and because people tend to believe what they see, false information can spread just as, if not more easily, than the truth.

“It’s certainly allowed more things to bubble up rather than flow from the top down,” says Berger. Absent gatekeepers, “everyone is their own media company, broadcasting to the particular set of people that follow them. It used to be that a major label signing you was the path to stardom. Now artists can build their own following online and break through that way. Social media has certainly made fame and attention more democratic, though not always in a good way.”

Deibert writes that “in a short period of time, digital technologies have become pervasive and deeply embedded in all that we do. Unwinding them completely is neither possible nor desirable.”

His cri de coeur argues: that citizens have the right to know what companies and governments are doing with their personal data, and that this right be extended internationally to hold autocratic regimes to account; that companies be barred from selling products and services that enable infringements on human rights and harms to civil society; for the creation of independent agencies with real power to hold social-media platforms to account; and the creation and enforcement of strong antitrust laws to end dominance of a very few social-media companies.

“Social media has certainly made fame and attention more democratic, though not always in a good way.” –Jonah Berger

The rising tide of concern is now extending across sectors. The U.S. Justice Department has recently begun an anti-trust investigation into how tech companies operate in social media, search, and retail services. In July, the John S. and James L. Knight Foundation announced the award of nearly $50 million in new funding to 11 U.S. universities to research how technology is transforming democracy. The foundation is also soliciting additional grant proposals to fund policy and legal research into the “rules, norms, and governance” that should be applied to social media and technology companies.

Given all of the reasons not to engage with social media — the privacy issues, the slippery-slope addiction aspect of it, its role in spreading incivility — do we want to try to put the genie back in the bottle? Can we? Does social media definitely have a future?

“Yes, surely it does,” says Yildirim. “Social connections are fabrics of society. Just as the telegraph or telephone as an innovation of communication did not reduce social connectivity, online social networks did not either. If anything, it likely increased connectivity, or reduced the cost of communicating with others.”

It is thanks to online social networks that individuals likely have larger social networks, she says, and while many criticize the fact that we are in touch with large numbers of individuals in a superficial way, these light connections may nevertheless be contributing to our lives when it comes to economic and social outcomes — ranging from finding jobs to meeting new people.

“We are used to being in contact with more individuals, and it is easier to remain in contact with people we only met once. Giving up on this does not seem likely for humans,” she says. “The technology with which we keep in touch may change, may evolve, but we will have social connections and platforms which enable them. Facebook may be gone in 10 years, but there will be something else.”

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Social Media's Impact on Society

This article was updated on: 11/19/2021

Social media is an undeniable force in modern society. With over half the global population using social platforms, and the average person spending at least two hours scrolling through them every day , it can’t be overstated that our digital spaces have altered our lives as we knew them. From giving us new ways to come together and stay connected with the world around us, to providing outlets for self-expression, social media has fundamentally changed the way we initiate, build and maintain our relationships.

But while these digital communities have become commonplace in our daily lives, researchers are only beginning to understand the consequences of social media use on future generations. Social media models are changing every day, with major platforms like Meta and Instagram evolving into primary digital advertising spaces as much as social ones. A critical responsibility falls on marketers to spread messages that inform, rather than contribute to the sea of misinformation that thrives on social media.

Read on to see what’s on marketers’ minds when it comes to the impact of social media on society:

MENTAL HEALTH

You’ve likely heard about the negative impacts that social media can have on mental health. Experts are weighing in on the role that the algorithms and design of social platforms play in exasperating these concerns.

At SXSW 2019 , Aza Raskin, co-founder of the Center for Human Technology, talked about the “digital loneliness epidemic,” which focused on the rise of depression and loneliness as it relates to social media use. During the panel, Raskin spoke about the “infinite scroll,” the design principle that enables users to continuously scroll through their feeds, without ever having to decide whether to keep going—it’s hard to imagine what the bottom of a TikTok feed would look like, and that’s intentional. But with the knowledge that mental health concerns are undeniably linked to social media use, the dilemma we’re now facing is when does good design become inhumane design?

Arguably, Rankin’s term for social media use could now be renamed the “digital loneliness pandemic ” as the world faces unprecedented isolation during the COVID-19 outbreak. In 2020 the Ad Council released a study exploring factors that cause loneliness, and what can be done to alleviate it. Interestingly, our research found that while social isolation is one factor that can cause loneliness, 73% of respondents typically maintain interpersonal relationships via technology, including engaging with others on social media. Simply put, social media use can both contribute to and help mitigate feelings of isolation. So how do we address this Catch-22? We should ask ourselves how we can use social media as a platform to foster positive digital communities as young adults rely on it more and more to cope with isolation.

Findings like these have been useful as we reexamine the focuses of Ad Council campaigns. In May 2020, our iconic Seize the Awkward campaign launched new creative highlighting ways young people could use digital communications tools to stay connected and check in on one another’s mental health while practicing physical distancing. A year later, we launched another mental health initiative, Sound It Out , which harnesses the power of music to speak to 10-14-year-olds’ emotional wellbeing. Ad Council has seen the importance of spreading awareness around mental health concerns as they relate to social media consumption in young adults—who will become the next generation of marketers.

EXTREMISM & HATE

Another trend on experts’ minds is how the algorithms behind these massively influential social media platforms may contribute to the rise of extremism and online radicalization.

Major social networking sites have faced criticism over how their advanced algorithms can lead users to increasingly fringe content. These platforms are central to discussions around online extremism, as social forums have become spaces for extreme communities to form and build influence digitally. However, these platforms are responding to concerns and troubleshooting functionalities that have the potential to result in dangerous outcomes. Meta, for example, announced test prompts to provide anti-extremism resources and support for users it believes have been exposed to extremist content on their feeds.

But as extremist groups continue to turn to fringe chatrooms and the “dark web” that begin on social media, combing through the underbelly of the internet and stopping the spread of hateful narratives is a daunting task. Promoting public service messages around Racial Justice and Diversity & Inclusion are just some of the ways that Ad Council and other marketers are using these platforms to move the needle away from hateful messaging and use these platforms to change mindsets in a positive way.

PUBLIC HEALTH CRISES

Social media can be both a space to enlighten and spread messages of doubt. The information age we’re all living in has enabled marketers to intervene as educators and providers of informative messaging to all facets of the American public. And no time has this been more urgent than during the COVID-19 pandemic.

Public health efforts around mask mandates and vaccine rollouts have now become increasingly polarized issues. Social media platforms have turned into breeding grounds for spreading disinformation around vaccinations, and as a result, has contributed to vaccine hesitancy among the American public. Meta, Instagram, and other platforms have begun to flag certain messages as false, but the work of regulating misinformation, especially during a pandemic, will be an enduring problem. To combat this, Ad Council and the COVID Collaborative have put a particular emphasis on our historic COVID-19 Vaccine Education initiative, which has connected trusted messengers with the “uncommitted” American public who feel the most uncertainty around getting the vaccine.

Living during a global pandemic has only solidified a societal need for social media as a way to stay connected to the world at large. During the pandemic, these platforms have been used to promote hopeful and educational messages, like #AloneTogether , and ensures that social media marketing can act as a public service.

DIGITAL ACTIVISM

Beyond serving as an educational resource, social media has been the space for digital activism across a myriad of social justice issues. Movements like #MeToo and #BlackLivesMatter have gone viral thanks to the power of social media. What starts as a simple hashtag has resulted in real change, from passing sexual harassment legislation in response to #MeToo, to pushing for criminal justice reform because of BLM activists. In these cases, social media empowered likeminded people to organize around a specific cause in a way not possible before.

It’s impossible to separate the role of social media from the scalable impact that these movements have had on society. #MeToo and BLM are just two examples of movements that have sparked national attention due in large part to conversations that began on social media.

SO, WHAT DOES THIS MEAN FOR MARKETERS?

Social media is a great equalizer that allows for large-scale discourse and an endless, unfiltered stream of content. Looking beyond the repercussions for a generation born on social media, these platforms remain an essential way for marketers to reach their audiences.

Whether you argue there are more benefits or disadvantages to a world run on social media, we can all agree that social media has fundamentally shifted how society communicates. With every scroll, view, like, comment and share, we’re taught something new about the impact of social media on the way we think and see the world.

But until we find a way to hold platforms more accountable for the global consequences of social media use, it’s up to marketers to use these digital resources as engines of progressive messaging. We can’t control the adverse effects of the Internet, but as marketers, we can do our part in ensuring that the right messages are being spread and that social media remains a force for social good.

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Why social media has changed the world — and how to fix it

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Are you on social media a lot? When is the last time you checked Twitter, Facebook, or Instagram? Last night? Before breakfast? Five minutes ago?

If so, you are not alone — which is the point, of course. Humans are highly social creatures. Our brains have become wired to process social information, and we usually feel better when we are connected. Social media taps into this tendency.

“Human brains have essentially evolved because of sociality more than any other thing,” says Sinan Aral, an MIT professor and expert in information technology and marketing. “When you develop a population-scale technology that delivers social signals to the tune of trillions per day in real-time, the rise of social media isn’t unexpected. It’s like tossing a lit match into a pool of gasoline.”

The numbers make this clear. In 2005, about 7 percent of American adults used social media. But by 2017, 80 percent of American adults used Facebook alone. About 3.5 billion people on the planet, out of 7.7 billion, are active social media participants. Globally, during a typical day, people post 500 million tweets, share over 10 billion pieces of Facebook content, and watch over a billion hours of YouTube video.

As social media platforms have grown, though, the once-prevalent, gauzy utopian vision of online community has disappeared. Along with the benefits of easy connectivity and increased information, social media has also become a vehicle for disinformation and political attacks from beyond sovereign borders.

“Social media disrupts our elections, our economy, and our health,” says Aral, who is the David Austin Professor of Management at the MIT Sloan School of Management.

Now Aral has written a book about it. In “The Hype Machine,” published this month by Currency, a Random House imprint, Aral details why social media platforms have become so successful yet so problematic, and suggests ways to improve them.

As Aral notes, the book covers some of the same territory as “The Social Dilemma,” a documentary that is one of the most popular films on Netflix at the moment. But Aral’s book, as he puts it, "starts where ‘The Social Dilemma’ leaves off and goes one step further to ask: What can we do about it?”

“This machine exists in every facet of our lives,” Aral says. “And the question in the book is, what do we do? How do we achieve the promise of this machine and avoid the peril? We’re at a crossroads. What we do next is essential, so I want to equip people, policymakers, and platforms to help us achieve the good outcomes and avoid the bad outcomes.”

When “engagement” equals anger

“The Hype Machine” draws on Aral’s own research about social networks, as well as other findings, from the cognitive sciences, computer science, business, politics, and more. Researchers at the University of California at Los Angeles, for instance, have found that people obtain bigger hits of dopamine — the chemical in our brains highly bound up with motivation and reward — when their social media posts receive more likes.

At the same time, consider a 2018 MIT study by Soroush Vosoughi, an MIT PhD student and now an assistant professor of computer science at Dartmouth College; Deb Roy, MIT professor of media arts and sciences and executive director of the MIT Media Lab; and Aral, who has been studying social networking for 20 years. The three researchers found that on Twitter, from 2006 to 2017, false news stories were 70 percent more likely to be retweeted than true ones. Why? Most likely because false news has greater novelty value compared to the truth, and provokes stronger reactions — especially disgust and surprise.

In this light, the essential tension surrounding social media companies is that their platforms gain audiences and revenue when posts provoke strong emotional responses, often based on dubious content.

“This is a well-designed, well-thought-out machine that has objectives it maximizes,” Aral says. “The business models that run the social-media industrial complex have a lot to do with the outcomes we’re seeing — it’s an attention economy, and businesses want you engaged. How do they get engagement? Well, they give you little dopamine hits, and … get you riled up. That’s why I call it the hype machine. We know strong emotions get us engaged, so [that favors] anger and salacious content.”

From Russia to marketing

“The Hype Machine” explores both the political implications and business dimensions of social media in depth. Certainly social media is fertile terrain for misinformation campaigns. During the 2016 U.S. presidential election, Russia spread  false information to at least 126 million people on Facebook and another 20 million people on Insta­gram (which Facebook owns), and was responsible for 10 million tweets. About 44 percent of adult Americans visited a false news source in the final weeks of the campaign.

“I think we need to be a lot more vigilant than we are,” says Aral.

We do not know if Russia’s efforts altered the outcome of the 2016 election, Aral says, though they may have been fairly effective. Curiously, it is not clear if the same is true of most U.S. corporate engagement efforts.

As Aral examines, digital advertising on most big U.S. online platforms is often wildly ineffective, with academic studies showing that the “lift” generated by ad campaigns — the extent to which they affect consumer action — has been overstated by a factor of hundreds, in some cases. Simply counting clicks on ads is not enough. Instead, online engagement tends to be more effective among new consumers, and when it is targeted well; in that sense, there is a parallel between good marketing and guerilla social media campaigns.

“The two questions I get asked the most these days,” Aral says, “are, one, did Russia succeed in intervening in our democracy? And two, how do I measure the ROI [return on investment] from marketing investments? As I was writing this book, I realized the answer to those two questions is the same.”

Ideas for improvement

“The Hype Machine” has received praise from many commentators. Foster Provost, a professor at New York University’s Stern School of Business, says it is a “masterful integration of science, business, law, and policy.” Duncan Watts, a university professor at the University of Pennsylvania, says the book is “essential reading for anyone who wants to understand how we got here and how we can get somewhere better.”

In that vein, “The Hype Machine” has several detailed suggestions for improving social media. Aral favors automated and user-generated labeling of false news, and limiting revenue-collection that is based on false content. He also calls for firms to help scholars better research the issue of election interference.

Aral believes federal privacy measures could be useful, if we learn from the benefits and missteps of the General Data Protection Regulation (GDPR) in Europe and a new California law that lets consumers stop some data-sharing and allows people to find out what information companies have stored about them. He does not endorse breaking up Facebook, and suggests instead that the social media economy needs structural reform. He calls for data portability and interoperability, so “consumers would own their identities and could freely switch from one network to another.” Aral believes that without such fundamental changes, new platforms will simply replace the old ones, propelled by the network effects that drive the social-media economy.

“I do not advocate any one silver bullet,” says Aral, who emphasizes that changes in four areas together — money, code, norms, and laws — can alter the trajectory of the social media industry.

But if things continue without change, Aral adds, Facebook and the other social media giants risk substantial civic backlash and user burnout.

“If you get me angry and riled up, I might click more in the short term, but I might also grow really tired and annoyed by how this is making my life miserable, and I might turn you off entirely,” Aral observes. “I mean, that’s why we have a Delete Facebook movement, that’s why we have a Stop Hate for Profit movement. People are pushing back against the short-term vision, and I think we need to embrace this longer-term vision of a healthier communications ecosystem.”

Changing the social media giants can seem like a tall order. Still, Aral says, these firms are not necessarily destined for domination.

“I don’t think this technology or any other technology has some deterministic endpoint,” Aral says. “I want to bring us back to a more practical reality, which is that technology is what we make it, and we are abdicating our responsibility to steer technology toward good and away from bad. That is the path I try to illuminate in this book.”

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Press mentions.

Prof. Sinan Aral’s new book, “The Hype Machine,” has been selected as one of the best books of the year about AI by Wired . Gilad Edelman notes that Aral’s book is “an engagingly written shortcut to expertise on what the likes of Facebook and Twitter are doing to our brains and our society.”

Prof. Sinan Aral speaks with Danny Crichton of TechCrunch about his new book, “The Hype Machine,” which explores the future of social media. Aral notes that he believes a starting point “for solving the social media crisis is creating competition in the social media economy.” 

New York Times

Prof. Sinan Aral speaks with New York Times editorial board member Greg Bensinger about how social media platforms can reduce the spread of misinformation. “Human-in-the-loop moderation is the right solution,” says Aral. “It’s not a simple silver bullet, but it would give accountability where these companies have in the past blamed software.”

Prof. Sinan Aral speaks with Kara Miller of GBH’s Innovation Hub about his research examining the impact of social media on everything from business re-openings during the Covid-19 pandemic to politics.

Prof. Sinan Aral speaks with NPR’s Michael Martin about his new book, “The Hype Machine,” which explores the benefits and downfalls posed by social media. “I've been researching social media for 20 years. I've seen its evolution and also the techno utopianism and dystopianism,” says Aral. “I thought it was appropriate to have a book that asks, 'what can we do to really fix the social media morass we find ourselves in?'”

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Feature Article — Dissecting Social Media: What You Should Know

Published on Aug 11, 2020

Parents PACK

Have you checked your Facebook News Feed recently? Watched a YouTube video? Posted on Instagram? Sent a Tweet? If so, you are among the 3.5 billion people worldwide who actively use social media.

Social media users generate a massive amount of information, from personal posts, photos and videos, to blogs, DIY articles and much more. While some content aims to entertain or inform, other information is intentionally meant to mislead or deceive. Those who intend to mislead rely on people sharing their messages to spread misinformation. As a result, it’s important to critically evaluate any information you see before sharing it further.

So, how can you tell which information is valid and which is not?

Read on to find some simple tips for checking posts. With a quick review, not only can you learn more about the reliability of what you are seeing, you can also help decrease the amount of bad information received by those in your network.

Looking at the parts of a post

1.  headline.

• Does the headline sound true or was it designed to be sensational?
• Does the headline agree with the content of the story?
• Is the headline funny or satirical?

Example: “The CDC has adjusted their COVID19 deaths from 64,000 to 37,000. What do you think about that? Still scared? Angry yet?”

This headline appeared in a Facebook post to support a conspiracy theory that the pandemic is a hoax. FactCheck.org explained that the adjustments were the result of two lists maintained by the Centers for Disease Control and Prevention (CDC) and why they were not in sync.

• Who wrote the post? If it is anonymous, this should raise a red flag.
• What do you know about the author? Is this an individual or someone representing an organization?
• Does the author claim to be an expert? Do the author’s credentials back up the claim?
• Does the author have an online profile? What kind of photo do they use on their profile? What is their screen name?
• Is the author selling something related to the topic?

Example: “OSHA 10&30 certified”

Several social media posts about the effectiveness of wearing face masks have misrepresented information provided by the Occupational Safety and Health Administration (OSHA). In one of them, shown on Snopes , the author claimed to be “OSHA 10&30 certified,” but OSHA confirmed that while they have training courses of 10 and 30 hours, the courses do not provide “certification,” nor do they cover COVID-19. In this case, the author was presenting misleading qualifications to sound like an expert.

In many cases, information will not come from the original source; it may have been forwarded by someone else in a person’s network. Often, people assume that because the person who sent it to them is reliable, they can trust the information. But, since not everyone checks the credibility of information before sharing it, users should be wary of any post. For these reasons, you will want to try to determine the original source:

• Who originally posted the information? Information shared on social media can be traced back to an original publication source by either clicking on the post or by searching for the original source online.
• How long has the source existed? New sources that have appeared to address a controversial issue might have a hidden agenda.
• Author’s name
• Publication date
• Organization’s mission and purpose
• Contact information
• Physical address
• Current copyright date
• Accurate reporting supported by evidence
• Links to other sources that back up the claim

If you can’t find the source or are not sure if the information is credible, it is best not to share it.

Example:  “And the people stayed home” poem attributed to an author who lived through the 1918 influenza pandemic

A poem that went viral during the COVID-19 pandemic was misattributed to an author who lived through the “Spanish flu pandemic of 1919.” When Snopes traced back the original source of “And the people stayed home,” it found that the author wrote the poem in 2020 about the COVID-19 pandemic, not the 1918 Spanish flu.

• When was the post originally published? Is it recent? Old information often resurfaces on social media when it appears timely, so it is useful to check the date.
• Does the author seem biased?
• What evidence is offered to support the claims being made? If the author doesn’t offer evidence or if the “evidence” is only anecdotes or opinions, seek other sources for more information before believing what is being shared.
• Can the quotes be attributed to legitimate people? Are those people informed about the topic?
• What is the quality of the writing? Often, articles with noticeable typos or grammatical errors are a sign that the post is not legitimate.
• What do other sources say about this topic? The more outlandish something seems, the more important it is to see if other sources are reporting the same thing. Even when consuming legitimate news, it is important to check the story from a few different sources because they will have different viewpoints and may cover different details, which will allow you to piece together a more complete picture of the situation.
• Has the issue been addressed by fact checkers? Sites like FactCheck.org , PolitiFact.com and Snopes.com are just a few of the websites dedicated to fact-checking.

Example: Plandemic: The Hidden Agenda Behind COVID-19 documentary

When Plandemic: The Hidden Agenda Behind COVID-19 went viral with outlandish claims about SARS-CoV-2, fact-checkers got busy scrutinizing the content. Both PolitiFact and FactCheck.org highlighted a host of false and misleading claims related to the novel coronavirus pandemic, including its origins, vaccines, treatments and more. Plandemic had more than 8 million views in the first week of its release.

Visuals are increasingly becoming an issue as more people edit images to make them align with a particular viewpoint of the story being told. This is especially true of those who intend to misinform or deceive.

• Does the photo appear shocking, particularly engaging, or simply out of place? Try using Google Images or TinEye to find the original photo. In particular, look for any signs that the image has been altered, such as people or things that were not part of the original photo.
• When and where was the original photo taken? Often old images are used to represent current topics, particularly on social media.
• Is a video or audio soundbite being used? If so, try to find the original video or recording so you can evaluate the context for which it was meant.

Example: Bill & Melinda Gates Foundation building

A side-by-side comparison of an original photo of the exterior of a Bill & Melinda Gates Foundation building alongside a doctored photo clearly shows alterations. A quick Google Image search brings up many original, unaltered copies of the photo.

In conclusion, as you use these tips more often, you will get faster and better at recognizing misinformation and deception. By thinking critically, looking for the small details, listening to different perspectives, and fact-checking, the spread of misinformation can stop with you.

Download a PDF version of this article.

For more information

Fact-checking websites.

• FactCheck.org
• The Washington Post Fact Checker

Additional resources

• News Literacy Project (NLP) — Provides information for educators and the public to help them become active consumers of news and information.
• Informable mobile App — A free app by the News Literacy Project aims to help players practice differentiating between good and bad information they find online.
• AllSides — Provides media bias ratings for hundreds of media outlets and writers to help the public identify different perspectives.

Categories: Parents PACK August 2020 , Feature Article

Materials in this section are updated as new information and vaccines become available. The Vaccine Education Center staff regularly reviews materials for accuracy.

You should not consider the information in this site to be specific, professional medical advice for your personal health or for your family's personal health. You should not use it to replace any relationship with a physician or other qualified healthcare professional. For medical concerns, including decisions about vaccinations, medications and other treatments, you should always consult your physician or, in serious cases, seek immediate assistance from emergency personnel.

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How Does Social Media Affect Your Mental Health?

Facebook has delayed the development of an Instagram app for children amid questions about its harmful effects on young people’s mental health. Does social media have an impact on your well-being?

By Nicole Daniels

What is your relationship with social media like? Which platforms do you spend the most time on? Which do you stay away from? How often do you log on?

What do you notice about your mental health and well-being when spending time on social networks?

In “ Facebook Delays Instagram App for Users 13 and Younger ,” Adam Satariano and Ryan Mac write about the findings of an internal study conducted by Facebook and what they mean for the Instagram Kids app that the company was developing:

Facebook said on Monday that it had paused development of an Instagram Kids service that would be tailored for children 13 years old or younger, as the social network increasingly faces questions about the app’s effect on young people’s mental health. The pullback preceded a congressional hearing this week about internal research conducted by Facebook , and reported in The Wall Street Journal , that showed the company knew of the harmful mental health effects that Instagram was having on teenage girls. The revelations have set off a public relations crisis for the Silicon Valley company and led to a fresh round of calls for new regulation. Facebook said it still wanted to build an Instagram product intended for children that would have a more “age appropriate experience,” but was postponing the plans in the face of criticism.

The article continues:

With Instagram Kids, Facebook had argued that young people were using the photo-sharing app anyway, despite age-requirement rules, so it would be better to develop a version more suitable for them. Facebook said the “kids” app was intended for ages 10 to 12 and would require parental permission to join, forgo ads and carry more age-appropriate content and features. Parents would be able to control what accounts their child followed. YouTube, which Google owns, has released a children’s version of its app. But since BuzzFeed broke the news this year that Facebook was working on the app, the company has faced scrutiny. Policymakers, regulators, child safety groups and consumer rights groups have argued that it hooks children on the app at a younger age rather than protecting them from problems with the service, including child predatory grooming, bullying and body shaming.

The article goes on to quote Adam Mosseri, the head of Instagram:

Mr. Mosseri said on Monday that the “the project leaked way before we knew what it would be” and that the company had “few answers” for the public at the time. Opposition to Facebook’s plans gained momentum this month when The Journal published articles based on leaked internal documents that showed Facebook knew about many of the harms it was causing. Facebook’s internal research showed that Instagram, in particular, had caused teen girls to feel worse about their bodies and led to increased rates of anxiety and depression, even while company executives publicly tried to minimize the app’s downsides.

But concerns about the effect of social media on young people go beyond Instagram Kids, the article notes:

A children’s version of Instagram would not fix more systemic problems, said Al Mik, a spokesman for 5Rights Foundation, a London group focused on digital rights issues for children. The group published a report in July showing that children as young as 13 were targeted within 24 hours of creating an account with harmful content, including material related to eating disorders, extreme diets, sexualized imagery, body shaming, self-harm and suicide. “Big Tobacco understood that the younger you got to someone, the easier you could get them addicted to become a lifelong user,” Doug Peterson, Nebraska’s attorney general, said in an interview. “I see some comparisons to social media platforms.” In May, attorneys general from 44 states and jurisdictions had signed a letter to Facebook’s chief executive, Mark Zuckerberg, asking him to end plans for building an Instagram app for children. American policymakers should pass tougher laws to restrict how tech platforms target children, said Josh Golin, executive director of Fairplay, a Boston-based group that was part of an international coalition of children’s and consumer groups opposed to the new app. Last year, Britain adopted an Age Appropriate Design Code , which requires added privacy protections for digital services used by people under the age of 18.

Students, read the entire article , then tell us:

Do you think Facebook made the right decision in halting the development of the Instagram Kids app? Do you think there should be social media apps for children 13 and younger? Why or why not?

What is your reaction to the research that found that Instagram can have harmful mental health effects on teenagers, particularly teenage girls? Have you experienced body image issues, anxiety or depression tied to your use of the app? How do you think social media affects your mental health?

What has your experience been on different social media apps? Are there apps that have a more positive or negative effect on your well-being? What do you think could explain these differences?

Have you ever been targeted with inappropriate or harmful content on Instagram or other social media apps? What responsibility do you think social media companies have to address these issues? Do you think there should be more protections in place for users under 18? Why or why not?

What does healthy social media engagement look like for you? What habits do you have around social media that you feel proud of? What behaviors would you like to change? How involved are your parents in your social media use? How involved do you think they should be?

If you were in charge of making Instagram, or another social media app, safer for teenagers, what changes would you make?

Want more writing prompts? You can find all of our questions in our Student Opinion column . Teachers, check out this guide to learn how you can incorporate them into your classroom.

Students 13 and older in the United States and Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public.

Nicole Daniels joined The Learning Network as a staff editor in 2019 after working in museum education, curriculum writing and bilingual education. More about Nicole Daniels

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Science News

Social media harms teens’ mental health, mounting evidence shows. what now.

Understanding what is going on in teens’ minds is necessary for targeted policy suggestions

Most teens use social media, often for hours on end. Some social scientists are confident that such use is harming their mental health. Now they want to pinpoint what explains the link.

Carol Yepes/Getty Images

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By Sujata Gupta

February 20, 2024 at 7:30 am

In January, Mark Zuckerberg, CEO of Facebook’s parent company Meta, appeared at a congressional hearing to answer questions about how social media potentially harms children. Zuckerberg opened by saying: “The existing body of scientific work has not shown a causal link between using social media and young people having worse mental health.”

But many social scientists would disagree with that statement. In recent years, studies have started to show a causal link between teen social media use and reduced well-being or mood disorders, chiefly depression and anxiety.

Ironically, one of the most cited studies into this link focused on Facebook.

Researchers delved into whether the platform’s introduction across college campuses in the mid 2000s increased symptoms associated with depression and anxiety. The answer was a clear yes , says MIT economist Alexey Makarin, a coauthor of the study, which appeared in the November 2022 American Economic Review . “There is still a lot to be explored,” Makarin says, but “[to say] there is no causal evidence that social media causes mental health issues, to that I definitely object.”

The concern, and the studies, come from statistics showing that social media use in teens ages 13 to 17 is now almost ubiquitous. Two-thirds of teens report using TikTok, and some 60 percent of teens report using Instagram or Snapchat, a 2022 survey found. (Only 30 percent said they used Facebook.) Another survey showed that girls, on average, allot roughly 3.4 hours per day to TikTok, Instagram and Facebook, compared with roughly 2.1 hours among boys. At the same time, more teens are showing signs of depression than ever, especially girls ( SN: 6/30/23 ).

As more studies show a strong link between these phenomena, some researchers are starting to shift their attention to possible mechanisms. Why does social media use seem to trigger mental health problems? Why are those effects unevenly distributed among different groups, such as girls or young adults? And can the positives of social media be teased out from the negatives to provide more targeted guidance to teens, their caregivers and policymakers?

“You can’t design good public policy if you don’t know why things are happening,” says Scott Cunningham, an economist at Baylor University in Waco, Texas.

Increasing rigor

Concerns over the effects of social media use in children have been circulating for years, resulting in a massive body of scientific literature. But those mostly correlational studies could not show if teen social media use was harming mental health or if teens with mental health problems were using more social media.

Moreover, the findings from such studies were often inconclusive, or the effects on mental health so small as to be inconsequential. In one study that received considerable media attention, psychologists Amy Orben and Andrew Przybylski combined data from three surveys to see if they could find a link between technology use, including social media, and reduced well-being. The duo gauged the well-being of over 355,000 teenagers by focusing on questions around depression, suicidal thinking and self-esteem.

Digital technology use was associated with a slight decrease in adolescent well-being , Orben, now of the University of Cambridge, and Przybylski, of the University of Oxford, reported in 2019 in Nature Human Behaviour . But the duo downplayed that finding, noting that researchers have observed similar drops in adolescent well-being associated with drinking milk, going to the movies or eating potatoes.

Holes have begun to appear in that narrative thanks to newer, more rigorous studies.

In one longitudinal study, researchers — including Orben and Przybylski — used survey data on social media use and well-being from over 17,400 teens and young adults to look at how individuals’ responses to a question gauging life satisfaction changed between 2011 and 2018. And they dug into how the responses varied by gender, age and time spent on social media.

Social media use was associated with a drop in well-being among teens during certain developmental periods, chiefly puberty and young adulthood, the team reported in 2022 in Nature Communications . That translated to lower well-being scores around ages 11 to 13 for girls and ages 14 to 15 for boys. Both groups also reported a drop in well-being around age 19. Moreover, among the older teens, the team found evidence for the Goldilocks Hypothesis: the idea that both too much and too little time spent on social media can harm mental health.

“There’s hardly any effect if you look over everybody. But if you look at specific age groups, at particularly what [Orben] calls ‘windows of sensitivity’ … you see these clear effects,” says L.J. Shrum, a consumer psychologist at HEC Paris who was not involved with this research. His review of studies related to teen social media use and mental health is forthcoming in the Journal of the Association for Consumer Research.

Cause and effect

That longitudinal study hints at causation, researchers say. But one of the clearest ways to pin down cause and effect is through natural or quasi-experiments. For these in-the-wild experiments, researchers must identify situations where the rollout of a societal “treatment” is staggered across space and time. They can then compare outcomes among members of the group who received the treatment to those still in the queue — the control group.

That was the approach Makarin and his team used in their study of Facebook. The researchers homed in on the staggered rollout of Facebook across 775 college campuses from 2004 to 2006. They combined that rollout data with student responses to the National College Health Assessment, a widely used survey of college students’ mental and physical health.

The team then sought to understand if those survey questions captured diagnosable mental health problems. Specifically, they had roughly 500 undergraduate students respond to questions both in the National College Health Assessment and in validated screening tools for depression and anxiety. They found that mental health scores on the assessment predicted scores on the screenings. That suggested that a drop in well-being on the college survey was a good proxy for a corresponding increase in diagnosable mental health disorders. 

Compared with campuses that had not yet gained access to Facebook, college campuses with Facebook experienced a 2 percentage point increase in the number of students who met the diagnostic criteria for anxiety or depression, the team found.

When it comes to showing a causal link between social media use in teens and worse mental health, “that study really is the crown jewel right now,” says Cunningham, who was not involved in that research.

A need for nuance

The social media landscape today is vastly different than the landscape of 20 years ago. Facebook is now optimized for maximum addiction, Shrum says, and other newer platforms, such as Snapchat, Instagram and TikTok, have since copied and built on those features. Paired with the ubiquity of social media in general, the negative effects on mental health may well be larger now.

Moreover, social media research tends to focus on young adults — an easier cohort to study than minors. That needs to change, Cunningham says. “Most of us are worried about our high school kids and younger.” 

And so, researchers must pivot accordingly. Crucially, simple comparisons of social media users and nonusers no longer make sense. As Orben and Przybylski’s 2022 work suggested, a teen not on social media might well feel worse than one who briefly logs on. 

Researchers must also dig into why, and under what circumstances, social media use can harm mental health, Cunningham says. Explanations for this link abound. For instance, social media is thought to crowd out other activities or increase people’s likelihood of comparing themselves unfavorably with others. But big data studies, with their reliance on existing surveys and statistical analyses, cannot address those deeper questions. “These kinds of papers, there’s nothing you can really ask … to find these plausible mechanisms,” Cunningham says.

One ongoing effort to understand social media use from this more nuanced vantage point is the SMART Schools project out of the University of Birmingham in England. Pedagogical expert Victoria Goodyear and her team are comparing mental and physical health outcomes among children who attend schools that have restricted cell phone use to those attending schools without such a policy. The researchers described the protocol of that study of 30 schools and over 1,000 students in the July BMJ Open.

Goodyear and colleagues are also combining that natural experiment with qualitative research. They met with 36 five-person focus groups each consisting of all students, all parents or all educators at six of those schools. The team hopes to learn how students use their phones during the day, how usage practices make students feel, and what the various parties think of restrictions on cell phone use during the school day.

Talking to teens and those in their orbit is the best way to get at the mechanisms by which social media influences well-being — for better or worse, Goodyear says. Moving beyond big data to this more personal approach, however, takes considerable time and effort. “Social media has increased in pace and momentum very, very quickly,” she says. “And research takes a long time to catch up with that process.”

Until that catch-up occurs, though, researchers cannot dole out much advice. “What guidance could we provide to young people, parents and schools to help maintain the positives of social media use?” Goodyear asks. “There’s not concrete evidence yet.”

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Effects of Social Media Use on Psychological Well-Being: A Mediated Model

Dragana ostic.

1 School of Finance and Economics, Jiangsu University, Zhenjiang, China

Sikandar Ali Qalati

Belem barbosa.

2 Research Unit of Governance, Competitiveness, and Public Policies (GOVCOPP), Center for Economics and Finance (cef.up), School of Economics and Management, University of Porto, Porto, Portugal

Syed Mir Muhammad Shah

3 Department of Business Administration, Sukkur Institute of Business Administration (IBA) University, Sukkur, Pakistan

Esthela Galvan Vela

4 CETYS Universidad, Tijuana, Mexico

Ahmed Muhammad Herzallah

5 Department of Business Administration, Al-Quds University, Jerusalem, Israel

6 Business School, Shandong University, Weihai, China

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The growth in social media use has given rise to concerns about the impacts it may have on users' psychological well-being. This paper's main objective is to shed light on the effect of social media use on psychological well-being. Building on contributions from various fields in the literature, it provides a more comprehensive study of the phenomenon by considering a set of mediators, including social capital types (i.e., bonding social capital and bridging social capital), social isolation, and smartphone addiction. The paper includes a quantitative study of 940 social media users from Mexico, using structural equation modeling (SEM) to test the proposed hypotheses. The findings point to an overall positive indirect impact of social media usage on psychological well-being, mainly due to the positive effect of bonding and bridging social capital. The empirical model's explanatory power is 45.1%. This paper provides empirical evidence and robust statistical analysis that demonstrates both positive and negative effects coexist, helping to reconcile the inconsistencies found so far in the literature.

Introduction

The use of social media has grown substantially in recent years (Leong et al., 2019 ; Kemp, 2020 ). Social media refers to “the websites and online tools that facilitate interactions between users by providing them opportunities to share information, opinions, and interest” (Swar and Hameed, 2017 , p. 141). Individuals use social media for many reasons, including entertainment, communication, and searching for information. Notably, adolescents and young adults are spending an increasing amount of time on online networking sites, e-games, texting, and other social media (Twenge and Campbell, 2019 ). In fact, some authors (e.g., Dhir et al., 2018 ; Tateno et al., 2019 ) have suggested that social media has altered the forms of group interaction and its users' individual and collective behavior around the world.

Consequently, there are increased concerns regarding the possible negative impacts associated with social media usage addiction (Swar and Hameed, 2017 ; Kircaburun et al., 2020 ), particularly on psychological well-being (Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ). Smartphones sometimes distract their users from relationships and social interaction (Chotpitayasunondh and Douglas, 2016 ; Li et al., 2020a ), and several authors have stressed that the excessive use of social media may lead to smartphone addiction (Swar and Hameed, 2017 ; Leong et al., 2019 ), primarily because of the fear of missing out (Reer et al., 2019 ; Roberts and David, 2020 ). Social media usage has been associated with anxiety, loneliness, and depression (Dhir et al., 2018 ; Reer et al., 2019 ), social isolation (Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ), and “phubbing,” which refers to the extent to which an individual uses, or is distracted by, their smartphone during face-to-face communication with others (Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ).

However, social media use also contributes to building a sense of connectedness with relevant others (Twenge and Campbell, 2019 ), which may reduce social isolation. Indeed, social media provides several ways to interact both with close ties, such as family, friends, and relatives, and weak ties, including coworkers, acquaintances, and strangers (Chen and Li, 2017 ), and plays a key role among people of all ages as they exploit their sense of belonging in different communities (Roberts and David, 2020 ). Consequently, despite the fears regarding the possible negative impacts of social media usage on well-being, there is also an increasing number of studies highlighting social media as a new communication channel (Twenge and Campbell, 2019 ; Barbosa et al., 2020 ), stressing that it can play a crucial role in developing one's presence, identity, and reputation, thus facilitating social interaction, forming and maintaining relationships, and sharing ideas (Carlson et al., 2016 ), which consequently may be significantly correlated to social support (Chen and Li, 2017 ; Holliman et al., 2021 ). Interestingly, recent studies (e.g., David et al., 2018 ; Bano et al., 2019 ; Barbosa et al., 2020 ) have suggested that the impact of smartphone usage on psychological well-being depends on the time spent on each type of application and the activities that users engage in.

Hence, the literature provides contradictory cues regarding the impacts of social media on users' well-being, highlighting both the possible negative impacts and the social enhancement it can potentially provide. In line with views on the need to further investigate social media usage (Karikari et al., 2017 ), particularly regarding its societal implications (Jiao et al., 2017 ), this paper argues that there is an urgent need to further understand the impact of the time spent on social media on users' psychological well-being, namely by considering other variables that mediate and further explain this effect.

One of the relevant perspectives worth considering is that provided by social capital theory, which is adopted in this paper. Social capital theory has previously been used to study how social media usage affects psychological well-being (e.g., Bano et al., 2019 ). However, extant literature has so far presented only partial models of associations that, although statistically acceptable and contributing to the understanding of the scope of social networks, do not provide as comprehensive a vision of the phenomenon as that proposed within this paper. Furthermore, the contradictory views, suggesting both negative (e.g., Chotpitayasunondh and Douglas, 2016 ; Van Den Eijnden et al., 2016 ; Jiao et al., 2017 ; Whaite et al., 2018 ; Choi and Noh, 2019 ; Chatterjee, 2020 ) and positive impacts (Carlson et al., 2016 ; Chen and Li, 2017 ; Twenge and Campbell, 2019 ) of social media on psychological well-being, have not been adequately explored.

Given this research gap, this paper's main objective is to shed light on the effect of social media use on psychological well-being. As explained in detail in the next section, this paper explores the mediating effect of bonding and bridging social capital. To provide a broad view of the phenomenon, it also considers several variables highlighted in the literature as affecting the relationship between social media usage and psychological well-being, namely smartphone addiction, social isolation, and phubbing. The paper utilizes a quantitative study conducted in Mexico, comprising 940 social media users, and uses structural equation modeling (SEM) to test a set of research hypotheses.

This article provides several contributions. First, it adds to existing literature regarding the effect of social media use on psychological well-being and explores the contradictory indications provided by different approaches. Second, it proposes a conceptual model that integrates complementary perspectives on the direct and indirect effects of social media use. Third, it offers empirical evidence and robust statistical analysis that demonstrates that both positive and negative effects coexist, helping resolve the inconsistencies found so far in the literature. Finally, this paper provides insights on how to help reduce the potential negative effects of social media use, as it demonstrates that, through bridging and bonding social capital, social media usage positively impacts psychological well-being. Overall, the article offers valuable insights for academics, practitioners, and society in general.

The remainder of this paper is organized as follows. Section Literature Review presents a literature review focusing on the factors that explain the impact of social media usage on psychological well-being. Based on the literature review, a set of hypotheses are defined, resulting in the proposed conceptual model, which includes both the direct and indirect effects of social media usage on psychological well-being. Section Research Methodology explains the methodological procedures of the research, followed by the presentation and discussion of the study's results in section Results. Section Discussion is dedicated to the conclusions and includes implications, limitations, and suggestions for future research.

Literature Review

Putnam ( 1995 , p. 664–665) defined social capital as “features of social life – networks, norms, and trust – that enable participants to act together more effectively to pursue shared objectives.” Li and Chen ( 2014 , p. 117) further explained that social capital encompasses “resources embedded in one's social network, which can be assessed and used for instrumental or expressive returns such as mutual support, reciprocity, and cooperation.”

Putnam ( 1995 , 2000 ) conceptualized social capital as comprising two dimensions, bridging and bonding, considering the different norms and networks in which they occur. Bridging social capital refers to the inclusive nature of social interaction and occurs when individuals from different origins establish connections through social networks. Hence, bridging social capital is typically provided by heterogeneous weak ties (Li and Chen, 2014 ). This dimension widens individual social horizons and perspectives and provides extended access to resources and information. Bonding social capital refers to the social and emotional support each individual receives from his or her social networks, particularly from close ties (e.g., family and friends).

Overall, social capital is expected to be positively associated with psychological well-being (Bano et al., 2019 ). Indeed, Williams ( 2006 ) stressed that interaction generates affective connections, resulting in positive impacts, such as emotional support. The following sub-sections use the lens of social capital theory to explore further the relationship between the use of social media and psychological well-being.

Social Media Use, Social Capital, and Psychological Well-Being

The effects of social media usage on social capital have gained increasing scholarly attention, and recent studies have highlighted a positive relationship between social media use and social capital (Brown and Michinov, 2019 ; Tefertiller et al., 2020 ). Li and Chen ( 2014 ) hypothesized that the intensity of Facebook use by Chinese international students in the United States was positively related to social capital forms. A longitudinal survey based on the quota sampling approach illustrated the positive effects of social media use on the two social capital dimensions (Chen and Li, 2017 ). Abbas and Mesch ( 2018 ) argued that, as Facebook usage increases, it will also increase users' social capital. Karikari et al. ( 2017 ) also found positive effects of social media use on social capital. Similarly, Pang ( 2018 ) studied Chinese students residing in Germany and found positive effects of social networking sites' use on social capital, which, in turn, was positively associated with psychological well-being. Bano et al. ( 2019 ) analyzed the 266 students' data and found positive effects of WhatsApp use on social capital forms and the positive effect of social capital on psychological well-being, emphasizing the role of social integration in mediating this positive effect.

Kim and Kim ( 2017 ) stressed the importance of having a heterogeneous network of contacts, which ultimately enhances the potential social capital. Overall, the manifest and social relations between people from close social circles (bonding social capital) and from distant social circles (bridging social capital) are strengthened when they promote communication, social support, and the sharing of interests, knowledge, and skills, which are shared with other members. This is linked to positive effects on interactions, such as acceptance, trust, and reciprocity, which are related to the individuals' health and psychological well-being (Bekalu et al., 2019 ), including when social media helps to maintain social capital between social circles that exist outside of virtual communities (Ellison et al., 2007 ).

Grounded on the above literature, this study proposes the following hypotheses:

• H1a: Social media use is positively associated with bonding social capital.
• H1b: Bonding social capital is positively associated with psychological well-being.
• H2a: Social media use is positively associated with bridging social capital.
• H2b: Bridging social capital is positively associated with psychological well-being.

Social Media Use, Social Isolation, and Psychological Well-Being

Social isolation is defined as “a deficit of personal relationships or being excluded from social networks” (Choi and Noh, 2019 , p. 4). The state that occurs when an individual lacks true engagement with others, a sense of social belonging, and a satisfying relationship is related to increased mortality and morbidity (Primack et al., 2017 ). Those who experience social isolation are deprived of social relationships and lack contact with others or involvement in social activities (Schinka et al., 2012 ). Social media usage has been associated with anxiety, loneliness, and depression (Dhir et al., 2018 ; Reer et al., 2019 ), and social isolation (Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ). However, some recent studies have argued that social media use decreases social isolation (Primack et al., 2017 ; Meshi et al., 2020 ). Indeed, the increased use of social media platforms such as Facebook, WhatsApp, Instagram, and Twitter, among others, may provide opportunities for decreasing social isolation. For instance, the improved interpersonal connectivity achieved via videos and images on social media helps users evidence intimacy, attenuating social isolation (Whaite et al., 2018 ).

Chappell and Badger ( 1989 ) stated that social isolation leads to decreased psychological well-being, while Choi and Noh ( 2019 ) concluded that greater social isolation is linked to increased suicide risk. Schinka et al. ( 2012 ) further argued that, when individuals experience social isolation from siblings, friends, family, or society, their psychological well-being tends to decrease. Thus, based on the literature cited above, this study proposes the following hypotheses:

• H3a: Social media use is significantly associated with social isolation.
• H3b: Social isolation is negatively associated with psychological well-being.

Social Media Use, Smartphone Addiction, Phubbing, and Psychological Well-Being

Smartphone addiction refers to “an individuals' excessive use of a smartphone and its negative effects on his/her life as a result of his/her inability to control his behavior” (Gökçearslan et al., 2018 , p. 48). Regardless of its form, smartphone addiction results in social, medical, and psychological harm to people by limiting their ability to make their own choices (Chotpitayasunondh and Douglas, 2016 ). The rapid advancement of information and communication technologies has led to the concept of social media, e-games, and also to smartphone addiction (Chatterjee, 2020 ). The excessive use of smartphones for social media use, entertainment (watching videos, listening to music), and playing e-games is more common amongst people addicted to smartphones (Jeong et al., 2016 ). In fact, previous studies have evidenced the relationship between social use and smartphone addiction (Salehan and Negahban, 2013 ; Jeong et al., 2016 ; Swar and Hameed, 2017 ). In line with this, the following hypotheses are proposed:

• H4a: Social media use is positively associated with smartphone addiction.
• H4b: Smartphone addiction is negatively associated with psychological well-being.

While smartphones are bringing individuals closer, they are also, to some extent, pulling people apart (Tonacci et al., 2019 ). For instance, they can lead to individuals ignoring others with whom they have close ties or physical interactions; this situation normally occurs due to extreme smartphone use (i.e., at the dinner table, in meetings, at get-togethers and parties, and in other daily activities). This act of ignoring others is called phubbing and is considered a common phenomenon in communication activities (Guazzini et al., 2019 ; Chatterjee, 2020 ). Phubbing is also referred to as an act of snubbing others (Chatterjee, 2020 ). This term was initially used in May 2012 by an Australian advertising agency to describe the “growing phenomenon of individuals ignoring their families and friends who were called phubbee (a person who is a recipients of phubbing behavior) victim of phubber (a person who start phubbing her or his companion)” (Chotpitayasunondh and Douglas, 2018 ). Smartphone addiction has been found to be a determinant of phubbing (Kim et al., 2018 ). Other recent studies have also evidenced the association between smartphones and phubbing (Chotpitayasunondh and Douglas, 2016 ; Guazzini et al., 2019 ; Tonacci et al., 2019 ; Chatterjee, 2020 ). Vallespín et al. ( 2017 ) argued that phubbing behavior has a negative influence on psychological well-being and satisfaction. Furthermore, smartphone addiction is considered responsible for the development of new technologies. It may also negatively influence individual's psychological proximity (Chatterjee, 2020 ). Therefore, based on the above discussion and calls for the association between phubbing and psychological well-being to be further explored, this study proposes the following hypotheses:

• H5: Smartphone addiction is positively associated with phubbing.
• H6: Phubbing is negatively associated with psychological well-being.

Indirect Relationship Between Social Media Use and Psychological Well-Being

Beyond the direct hypotheses proposed above, this study investigates the indirect effects of social media use on psychological well-being mediated by social capital forms, social isolation, and phubbing. As described above, most prior studies have focused on the direct influence of social media use on social capital forms, social isolation, smartphone addiction, and phubbing, as well as the direct impact of social capital forms, social isolation, smartphone addiction, and phubbing on psychological well-being. Very few studies, however, have focused on and evidenced the mediating role of social capital forms, social isolation, smartphone addiction, and phubbing derived from social media use in improving psychological well-being (Chen and Li, 2017 ; Pang, 2018 ; Bano et al., 2019 ; Choi and Noh, 2019 ). Moreover, little is known about smartphone addiction's mediating role between social media use and psychological well-being. Therefore, this study aims to fill this gap in the existing literature by investigating the mediation of social capital forms, social isolation, and smartphone addiction. Further, examining the mediating influence will contribute to a more comprehensive understanding of social media use on psychological well-being via the mediating associations of smartphone addiction and psychological factors. Therefore, based on the above, we propose the following hypotheses (the conceptual model is presented in Figure 1 ):

Conceptual model.

• H7: (a) Bonding social capital; (b) bridging social capital; (c) social isolation; and (d) smartphone addiction mediate the relationship between social media use and psychological well-being.

Research Methodology

Sample procedure and online survey.

This study randomly selected students from universities in Mexico. We chose University students for the following reasons. First, students are considered the most appropriate sample for e-commerce studies, particularly in the social media context (Oghazi et al., 2018 ; Shi et al., 2018 ). Second, University students are considered to be frequent users and addicted to smartphones (Mou et al., 2017 ; Stouthuysen et al., 2018 ). Third, this study ensured that respondents were experienced, well-educated, and possessed sufficient knowledge of the drawbacks of social media and the extreme use of smartphones. A total sample size of 940 University students was ultimately achieved from the 1,500 students contacted, using a convenience random sampling approach, due both to the COVID-19 pandemic and budget and time constraints. Additionally, in order to test the model, a quantitative empirical study was conducted, using an online survey method to collect data. This study used a web-based survey distributed via social media platforms for two reasons: the COVID-19 pandemic; and to reach a large number of respondents (Qalati et al., 2021 ). Furthermore, online surveys are considered a powerful and authenticated tool for new research (Fan et al., 2021 ), while also representing a fast, simple, and less costly approach to collecting data (Dutot and Bergeron, 2016 ).

Data Collection Procedures and Respondent's Information

Data were collected by disseminating a link to the survey by e-mail and social network sites. Before presenting the closed-ended questionnaire, respondents were assured that their participation would remain voluntary, confidential, and anonymous. Data collection occurred from July 2020 to December 2020 (during the pandemic). It should be noted that, because data were collected during the pandemic, this may have had an influence on the results of the study. The reason for choosing a six-month lag time was to mitigate common method bias (CMB) (Li et al., 2020b ). In the present study, 1,500 students were contacted via University e-mail and social applications (Facebook, WhatsApp, and Instagram). We sent a reminder every month for 6 months (a total of six reminders), resulting in 940 valid responses. Thus, 940 (62.6% response rate) responses were used for hypotheses testing.

Table 1 reveals that, of the 940 participants, three-quarters were female (76.4%, n = 719) and nearly one-quarter (23.6%, n = 221) were male. Nearly half of the participants (48.8%, n = 459) were aged between 26 and 35 years, followed by 36 to 35 years (21.9%, n = 206), <26 (20.3%, n = 191), and over 45 (8.9%, n = 84). Approximately two-thirds (65%, n = 611) had a bachelor's degree or above, while one-third had up to 12 years of education. Regarding the daily frequency of using the Internet, nearly half (48.6%, n = 457) of the respondents reported between 5 and 8 h a day, and over one-quarter (27.2%) 9–12 h a day. Regarding the social media platforms used, over 38.5 and 39.6% reported Facebook and WhatsApp, respectively. Of the 940 respondents, only 22.1% reported Instagram (12.8%) and Twitter (9.2%). It should be noted, however, that the sample is predominantly female and well-educated.

Respondents' characteristics.

Measurement Items

The study used five-point Likert scales (1 = “strongly disagree;” 5 = “strongly agree”) to record responses.

Social Media Use

Social media use was assessed using four items adapted from Karikari et al. ( 2017 ). Sample items include “Social media is part of my everyday activity,” “Social media has become part of my daily life,” “I would be sorry if social media shut down,” and “I feel out of touch, when I have not logged onto social media for a while.” The adapted items had robust reliability and validity (CA = 783, CR = 0.857, AVE = 0.600).

Social Capital

Social capital was measured using a total of eight items, representing bonding social capital (four items) and bridging social capital (four items) adapted from Chan ( 2015 ). Sample construct items include: bonging social capital (“I am willing to spend time to support general community activities,” “I interact with people who are quite different from me”) and bridging social capital (“My social media community is a good place to be,” “Interacting with people on social media makes me want to try new things”). The adapted items had robust reliability and validity [bonding social capital (CA = 0.785, CR = 0.861, AVE = 0.608) and bridging social capital (CA = 0.834, CR = 0.883, AVE = 0.601)].

Social Isolation

Social isolation was assessed using three items from Choi and Noh ( 2019 ). Sample items include “I do not have anyone to play with,” “I feel alone from people,” and “I have no one I can trust.” This adapted scale had substantial reliability and validity (CA = 0.890, CR = 0.928, AVE = 0.811).

Smartphone Addiction

Smartphone addiction was assessed using five items taken from Salehan and Negahban ( 2013 ). Sample items include “I am always preoccupied with my mobile,” “Using my mobile phone keeps me relaxed,” and “I am not able to control myself from frequent use of mobile phones.” Again, these adapted items showed substantial reliability and validity (CA = 903, CR = 0.928, AVE = 0.809).

Phubbing was assessed using four items from Chotpitayasunondh and Douglas ( 2018 ). Sample items include: “I have conflicts with others because I am using my phone” and “I would rather pay attention to my phone than talk to others.” This construct also demonstrated significant reliability and validity (CA = 770, CR = 0.894, AVE = 0.809).

Psychological Well-Being

Psychological well-being was assessed using five items from Jiao et al. ( 2017 ). Sample items include “I lead a purposeful and meaningful life with the help of others,” “My social relationships are supportive and rewarding in social media,” and “I am engaged and interested in my daily on social media.” This study evidenced that this adapted scale had substantial reliability and validity (CA = 0.886, CR = 0.917, AVE = 0.688).

Data Analysis

Based on the complexity of the association between the proposed construct and the widespread use and acceptance of SmartPLS 3.0 in several fields (Hair et al., 2019 ), we utilized SEM, using SmartPLS 3.0, to examine the relationships between constructs. Structural equation modeling is a multivariate statistical analysis technique that is used to investigate relationships. Further, it is a combination of factor and multivariate regression analysis, and is employed to explore the relationship between observed and latent constructs.

SmartPLS 3.0 “is a more comprehensive software program with an intuitive graphical user interface to run partial least square SEM analysis, certainly has had a massive impact” (Sarstedt and Cheah, 2019 ). According to Ringle et al. ( 2015 ), this commercial software offers a wide range of algorithmic and modeling options, improved usability, and user-friendly and professional support. Furthermore, Sarstedt and Cheah ( 2019 ) suggested that structural equation models enable the specification of complex interrelationships between observed and latent constructs. Hair et al. ( 2019 ) argued that, in recent years, the number of articles published using partial least squares SEM has increased significantly in contrast to covariance-based SEM. In addition, partial least squares SEM using SmartPLS is more appealing for several scholars as it enables them to predict more complex models with several variables, indicator constructs, and structural paths, instead of imposing distributional assumptions on the data (Hair et al., 2019 ). Therefore, this study utilized the partial least squares SEM approach using SmartPLS 3.0.

Common Method Bias (CMB) Test

This study used the Kaiser–Meyer–Olkin (KMO) test to measure the sampling adequacy and ensure data suitability. The KMO test result was 0.874, which is greater than an acceptable threshold of 0.50 (Ali Qalati et al., 2021 ; Shrestha, 2021 ), and hence considered suitable for explanatory factor analysis. Moreover, Bartlett's test results demonstrated a significance level of 0.001, which is considered good as it is below the accepted threshold of 0.05.

The term CMB is associated with Campbell and Fiske ( 1959 ), who highlighted the importance of CMB and identified that a portion of variance in the research may be due to the methods employed. It occurs when all scales of the study are measured at the same time using a single questionnaire survey (Podsakoff and Organ, 1986 ); subsequently, estimates of the relationship among the variables might be distorted by the impacts of CMB. It is considered a serious issue that has a potential to “jeopardize” the validity of the study findings (Tehseen et al., 2017 ). There are several reasons for CMB: (1) it mainly occurs due to response “tendencies that raters can apply uniformity across the measures;” and (2) it also occurs due to similarities in the wording and structure of the survey items that produce similar results (Jordan and Troth, 2019 ). Harman's single factor test and a full collinearity approach were employed to ensure that the data was free from CMB (Tehseen et al., 2017 ; Jordan and Troth, 2019 ; Ali Qalati et al., 2021 ). Harman's single factor test showed a single factor explained only 22.8% of the total variance, which is far below the 50.0% acceptable threshold (Podsakoff et al., 2003 ).

Additionally, the variance inflation factor (VIF) was used, which is a measure of the amount of multicollinearity in a set of multiple regression constructs and also considered a way of detecting CMB (Hair et al., 2019 ). Hair et al. ( 2019 ) suggested that the acceptable threshold for the VIF is 3.0; as the computed VIFs for the present study ranged from 1.189 to 1.626, CMB is not a key concern (see Table 2 ). Bagozzi et al. ( 1991 ) suggested a correlation-matrix procedure to detect CMB. Common method bias is evident if correlation among the principle constructs is >0.9 (Tehseen et al., 2020 ); however, no values >0.9 were found in this study (see section Assessment of Measurement Model). This study used a two-step approach to evaluate the measurement model and the structural model.

Common method bias (full collinearity VIF).

Assessment of Measurement Model

Before conducting the SEM analysis, the measurement model was assessed to examine individual item reliability, internal consistency, and convergent and discriminant validity. Table 3 exhibits the values of outer loading used to measure an individual item's reliability (Hair et al., 2012 ). Hair et al. ( 2017 ) proposed that the value for each outer loading should be ≥0.7; following this principle, two items of phubbing (PHUB3—I get irritated if others ask me to get off my phone and talk to them; PHUB4—I use my phone even though I know it irritated others) were removed from the analysis Hair et al. ( 2019 ). According to Nunnally ( 1978 ), Cronbach's alpha values should exceed 0.7. The threshold values of constructs in this study ranged from 0.77 to 0.903. Regarding internal consistency, Bagozzi and Yi ( 1988 ) suggested that composite reliability (CR) should be ≥0.7. The coefficient value for CR in this study was between 0.857 and 0.928. Regarding convergent validity, Fornell and Larcker ( 1981 ) suggested that the average variance extracted (AVE) should be ≥0.5. Average variance extracted values in this study were between 0.60 and 0.811. Finally, regarding discriminant validity, according to Fornell and Larcker ( 1981 ), the square root of the AVE for each construct should exceed the inter-correlations of the construct with other model constructs. That was the case in this study, as shown in Table 4 .

Study measures, factor loading, and the constructs' reliability and convergent validity.

Discriminant validity and correlation.

Bold values are the square root of the AVE .

Hence, by analyzing the results of the measurement model, it can be concluded that the data are adequate for structural equation estimation.

Assessment of the Structural Model

This study used the PLS algorithm and a bootstrapping technique with 5,000 bootstraps as proposed by Hair et al. ( 2019 ) to generate the path coefficient values and their level of significance. The coefficient of determination ( R 2 ) is an important measure to assess the structural model and its explanatory power (Henseler et al., 2009 ; Hair et al., 2019 ). Table 5 and Figure 2 reveal that the R 2 value in the present study was 0.451 for psychological well-being, which means that 45.1% of changes in psychological well-being occurred due to social media use, social capital forms (i.e., bonding and bridging), social isolation, smartphone addiction, and phubbing. Cohen ( 1998 ) proposed that R 2 values of 0.60, 0.33, and 0.19 are considered substantial, moderate, and weak. Following Cohen's ( 1998 ) threshold values, this research demonstrates a moderate predicting power for psychological well-being among Mexican respondents ( Table 6 ).

Summary of path coefficients and hypothesis testing.

Structural model.

Strength of the model (Predictive relevance, coefficient of determination, and model fit indices).

Goodness of fit → SRMR = 0.063; d_ULS = 1.589; d_G = 0.512; chi-square = 2,910.744 .

Apart from the R 2 measure, the present study also used cross-validated redundancy measures, or effect sizes ( q 2 ), to assess the proposed model and validate the results (Ringle et al., 2012 ). Hair et al. ( 2019 ) suggested that a model exhibiting an effect size q 2 > 0 has predictive relevance ( Table 6 ). This study's results evidenced that it has a 0.15 <0.29 <0.35 (medium) predictive relevance, as 0.02, 0.15, and 0.35 are considered small, medium, and large, respectively (Cohen, 1998 ). Regarding the goodness-of-fit indices, Hair et al. ( 2019 ) suggested the standardized root mean square residual (SRMR) to evaluate the goodness of fit. Standardized root mean square is an absolute measure of fit: a value of zero indicates perfect fit and a value <0.08 is considered good fit (Hair et al., 2019 ). This study exhibits an adequate model fitness level with an SRMR value of 0.063 ( Table 6 ).

Table 5 reveals that all hypotheses of the study were accepted base on the criterion ( p -value < 0.05). H1a (β = 0.332, t = 10.283, p = 0.001) was confirmed, with the second most robust positive and significant relationship (between social media use and bonding social capital). In addition, this study evidenced a positive and significant relationship between bonding social capital and psychological well-being (β = 0.127, t = 4.077, p = 0.001); therefore, H1b was accepted. Regarding social media use and bridging social capital, the present study found the most robust positive and significant impact (β = 0.439, t = 15.543, p = 0.001); therefore, H2a was accepted. The study also evidenced a positive and significant association between bridging social capital and psychological well-being (β = 0.561, t = 20.953, p = 0.001); thus, H2b was accepted. The present study evidenced a significant effect of social media use on social isolation (β = 0.145, t = 4.985, p = 0.001); thus, H3a was accepted. In addition, this study accepted H3b (β = −0.051, t = 2.01, p = 0.044). Furthermore, this study evidenced a positive and significant effect of social media use on smartphone addiction (β = 0.223, t = 6.241, p = 0.001); therefore, H4a was accepted. Furthermore, the present study found that smartphone addiction has a negative significant influence on psychological well-being (β = −0.068, t = 2.387, p = 0.017); therefore, H4b was accepted. Regarding the relationship between smartphone addiction and phubbing, this study found a positive and significant effect of smartphone addiction on phubbing (β = 0.244, t = 7.555, p = 0.001); therefore, H5 was accepted. Furthermore, the present research evidenced a positive and significant influence of phubbing on psychological well-being (β = 0.137, t = 4.938, p = 0.001); therefore, H6 was accepted. Finally, the study provides interesting findings on the indirect effect of social media use on psychological well-being ( t -value > 1.96 and p -value < 0.05); therefore, H7a–d were accepted.

Furthermore, to test the mediating analysis, Preacher and Hayes's ( 2008 ) approach was used. The key characteristic of an indirect relationship is that it involves a third construct, which plays a mediating role in the relationship between the independent and dependent constructs. Logically, the effect of A (independent construct) on C (the dependent construct) is mediated by B (a third variable). Preacher and Hayes ( 2008 ) suggested the following: B is a construct acting as a mediator if A significantly influences B, A significantly accounts for variability in C, B significantly influences C when controlling for A, and the influence of A on C decreases significantly when B is added simultaneously with A as a predictor of C. According to Matthews et al. ( 2018 ), if the indirect effect is significant while the direct insignificant, full mediation has occurred, while if both direct and indirect effects are substantial, partial mediation has occurred. This study evidenced that there is partial mediation in the proposed construct ( Table 5 ). Following Preacher and Hayes ( 2008 ) this study evidenced that there is partial mediation in the proposed construct, because the relationship between independent variable (social media use) and dependent variable (psychological well-being) is significant ( p -value < 0.05) and indirect effect among them after introducing mediator (bonding social capital, bridging social capital, social isolation, and smartphone addiction) is also significant ( p -value < 0.05), therefore it is evidenced that when there is a significant effect both direct and indirect it's called partial mediation.

The present study reveals that the social and psychological impacts of social media use among University students is becoming more complex as there is continuing advancement in technology, offering a range of affordable interaction opportunities. Based on the 940 valid responses collected, all the hypotheses were accepted ( p < 0.05).

H1a finding suggests that social media use is a significant influencing factor of bonding social capital. This implies that, during a pandemic, social media use enables students to continue their close relationships with family members, friends, and those with whom they have close ties. This finding is in line with prior work of Chan ( 2015 ) and Ellison et al. ( 2007 ), who evidenced that social bonding capital is predicted by Facebook use and having a mobile phone. H1b findings suggest that, when individuals believe that social communication can help overcome obstacles to interaction and encourage more virtual self-disclosure, social media use can improve trust and promote the establishment of social associations, thereby enhancing well-being. These findings are in line with those of Gong et al. ( 2021 ), who also witnessed the significant effect of bonding social capital on immigrants' psychological well-being, subsequently calling for the further evidence to confirm the proposed relationship.

The findings of the present study related to H2a suggest that students are more likely to use social media platforms to receive more emotional support, increase their ability to mobilize others, and to build social networks, which leads to social belongingness. Furthermore, the findings suggest that social media platforms enable students to accumulate and maintain bridging social capital; further, online classes can benefit students who feel shy when participating in offline classes. This study supports the previous findings of Chan ( 2015 ) and Karikari et al. ( 2017 ). Notably, the present study is not limited to a single social networking platform, taking instead a holistic view of social media. The H2b findings are consistent with those of Bano et al. ( 2019 ), who also confirmed the link between bonding social capital and psychological well-being among University students using WhatsApp as social media platform, as well as those of Chen and Li ( 2017 ).

The H3a findings suggest that, during the COVID-19 pandemic when most people around the world have had limited offline or face-to-face interaction and have used social media to connect with families, friends, and social communities, they have often been unable to connect with them. This is due to many individuals avoiding using social media because of fake news, financial constraints, and a lack of trust in social media; thus, the lack both of offline and online interaction, coupled with negative experiences on social media use, enhances the level of social isolation (Hajek and König, 2021 ). These findings are consistent with those of Adnan and Anwar ( 2020 ). The H3b suggests that higher levels of social isolation have a negative impact on psychological well-being. These result indicating that, consistent with Choi and Noh ( 2019 ), social isolation is negatively and significantly related to psychological well-being.

The H4a results suggests that substantial use of social media use leads to an increase in smartphone addiction. These findings are in line with those of Jeong et al. ( 2016 ), who stated that the excessive use of smartphones for social media, entertainment (watching videos, listening to music), and playing e-games was more likely to lead to smartphone addiction. These findings also confirm the previous work of Jeong et al. ( 2016 ), Salehan and Negahban ( 2013 ), and Swar and Hameed ( 2017 ). The H4b results revealed that a single unit increase in smartphone addiction results in a 6.8% decrease in psychological well-being. These findings are in line with those of Tangmunkongvorakul et al. ( 2019 ), who showed that students with higher levels of smartphone addiction had lower psychological well-being scores. These findings also support those of Shoukat ( 2019 ), who showed that smartphone addiction inversely influences individuals' mental health.

This suggests that the greater the smartphone addiction, the greater the phubbing. The H5 findings are in line with those of Chatterjee ( 2020 ), Chotpitayasunondh and Douglas ( 2016 ), Guazzini et al. ( 2019 ), and Tonacci et al. ( 2019 ), who also evidenced a significant impact of smartphone addiction and phubbing. Similarly, Chotpitayasunondh and Douglas ( 2018 ) corroborated that smartphone addiction is the main predictor of phubbing behavior. However, these findings are inconsistent with those of Vallespín et al. ( 2017 ), who found a negative influence of phubbing.

The H6 results suggests that phubbing is one of the significant predictors of psychological well-being. Furthermore, these findings suggest that, when phubbers use a cellphone during interaction with someone, especially during the current pandemic, and they are connected with many family members, friends, and relatives; therefore, this kind of action gives them more satisfaction, which simultaneously results in increased relaxation and decreased depression (Chotpitayasunondh and Douglas, 2018 ). These findings support those of Davey et al. ( 2018 ), who evidenced that phubbing has a significant influence on adolescents and social health students in India.

The findings showed a significant and positive effect of social media use on psychological well-being both through bridging and bonding social capital. However, a significant and negative effect of social media use on psychological well-being through smartphone addiction and through social isolation was also found. Hence, this study provides evidence that could shed light on the contradictory contributions in the literature suggesting both positive (e.g., Chen and Li, 2017 ; Twenge and Campbell, 2019 ; Roberts and David, 2020 ) and negative (e.g., Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ) effects of social media use on psychological well-being. This study concludes that the overall impact is positive, despite some degree of negative indirect impact.

Theoretical Contributions

This study's findings contribute to the current literature, both by providing empirical evidence for the relationships suggested by extant literature and by demonstrating the relevance of adopting a more complex approach that considers, in particular, the indirect effect of social media on psychological well-being. As such, this study constitutes a basis for future research (Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ) aiming to understand the impacts of social media use and to find ways to reduce its possible negative impacts.

In line with Kim and Kim ( 2017 ), who stressed the importance of heterogeneous social networks in improving social capital, this paper suggests that, to positively impact psychological well-being, social media usage should be associated both with strong and weak ties, as both are important in building social capital, and hence associated with its bonding and bridging facets. Interestingly, though, bridging capital was shown as having the greatest impact on psychological well-being. Thus, the importance of wider social horizons, the inclusion in different groups, and establishing new connections (Putnam, 1995 , 2000 ) with heterogeneous weak ties (Li and Chen, 2014 ) are highlighted in this paper.

Practical Contributions

These findings are significant for practitioners, particularly those interested in dealing with the possible negative impacts of social media use on psychological well-being. Although social media use is associated with factors that negatively impact psychological well-being, particularly smartphone addiction and social isolation, these negative impacts can be lessened if the connections with both strong and weak ties are facilitated and featured by social media. Indeed, social media platforms offer several features, from facilitating communication with family, friends, and acquaintances, to identifying and offering access to other people with shared interests. However, it is important to access heterogeneous weak ties (Li and Chen, 2014 ) so that social media offers access to wider sources of information and new resources, hence enhancing bridging social capital.

Limitations and Directions for Future Studies

This study is not without limitations. For example, this study used a convenience sampling approach to reach to a large number of respondents. Further, this study was conducted in Mexico only, limiting the generalizability of the results; future research should therefore use a cross-cultural approach to investigate the impacts of social media use on psychological well-being and the mediating role of proposed constructs (e.g., bonding and bridging social capital, social isolation, and smartphone addiction). The sample distribution may also be regarded as a limitation of the study because respondents were mainly well-educated and female. Moreover, although Internet channels represent a particularly suitable way to approach social media users, the fact that this study adopted an online survey does not guarantee a representative sample of the population. Hence, extrapolating the results requires caution, and study replication is recommended, particularly with social media users from other countries and cultures. The present study was conducted in the context of mainly University students, primarily well-educated females, via an online survey on in Mexico; therefore, the findings represent a snapshot at a particular time. Notably, however, the effect of social media use is increasing due to COVID-19 around the globe and is volatile over time.

Two of the proposed hypotheses of this study, namely the expected negative impacts of social media use on social isolation and of phubbing on psychological well-being, should be further explored. One possible approach is to consider the type of connections (i.e., weak and strong ties) to explain further the impact of social media usage on social isolation. Apparently, the prevalence of weak ties, although facilitating bridging social capital, may have an adverse impact in terms of social isolation. Regarding phubbing, the fact that the findings point to a possible positive impact on psychological well-being should be carefully addressed, specifically by psychology theorists and scholars, in order to identify factors that may help further understand this phenomenon. Other suggestions for future research include using mixed-method approaches, as qualitative studies could help further validate the results and provide complementary perspectives on the relationships between the considered variables.

Data Availability Statement

Ethics statement.

The studies involving human participants were reviewed and approved by Jiangsu University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding. This study is supported by the National Statistics Research Project of China (2016LY96).

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Chapter 10: Social Media–Uses and Messaging

57 The impact of social media in strategic communication industries

The rise of social media has had significant effects on the strategic communication industry. Marketers use social media to enhance traditional efforts such as direct mail fliers and television advertisements. Social media also enable marketers to create interactive content for audiences. In the public relations field, social media give professionals easier access to journalists and news media outlets. For example, it is becoming common for public relations professionals to reach out to reporters via Twitter.

In many ways, social media have made it easier for consumers to hold organizations, public figures, and large institutions accountable (Green, 2012). Users can easily find and reveal information about a previous event involving an organization, whether it was advantageous or damaging to the brand. Users can also provide instant public feedback by voicing their opinions via social media networks. Furthermore, social media have made it challenging for many organizations to control their brand and present a consistent message across platforms. Audiences can generate information that can be damaging to a brand’s reputation. Take a look at this video from Sherry Lloyd, social media and marketing manager for Vineyard Columbus, who discusses brand management and the challenges of controlling a company’s identity in the social media age.

In-Depth Look at a Career in Brand Management with Sherry Lloyd

Many campaigns effectively use social media to produce beneficial effects. In 2011, KFC created a public relations campaign aimed at strengthening its relationship with young consumers and enhancing its brand reputation. The campaign launched a contest that awarded a $20,000 scholarship to an individual with the best tweet using the hashtag #KFCScholar. The contest generated more than 1,000 media placements, 2,800 applications, and a 20 percent increase in KFC’s following on Twitter (Black, 2011).  This example demonstrates the utility of using social media to create reputation and relationship management campaigns.

Writing for Strategic Communication Industries Copyright © 2016 by Jasmine Roberts is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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The future of social media in marketing

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• Published: 12 October 2019
• Volume 48 , pages 79–95, ( 2020 )

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• Gil Appel 1 ,
• Lauren Grewal 2 ,
• Rhonda Hadi 3 &
• Andrew T. Stephen 3 , 4  

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Social media allows people to freely interact with others and offers multiple ways for marketers to reach and engage with consumers. Considering the numerous ways social media affects individuals and businesses alike, in this article, the authors focus on where they believe the future of social media lies when considering marketing-related topics and issues. Drawing on academic research, discussions with industry leaders, and popular discourse, the authors identify nine themes, organized by predicted imminence (i.e., the immediate, near, and far futures), that they believe will meaningfully shape the future of social media through three lenses: consumer, industry, and public policy. Within each theme, the authors describe the digital landscape, present and discuss their predictions, and identify relevant future research directions for academics and practitioners.

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Introduction

Social media is used by billions of people around the world and has fast become one of the defining technologies of our time. Facebook, for example, reported having 2.38 billion monthly active users and 1.56 billion daily active users as of March 31, 2019 (Facebook 2019 ). Globally, the total number of social media users is estimated to grow to 3.29 billion users in 2022, which will be 42.3% of the world’s population (eMarketer 2018 ). Given the massive potential audience available who are spending many hours a day using social media across the various platforms, it is not surprising that marketers have embraced social media as a marketing channel. Academically, social media has also been embraced, and an extensive body of research on social media marketing and related topics, such as online word of mouth (WOM) and online networks, has been developed. Despite what academics and practitioners have studied and learned over the last 15–20 years on this topic, due to the fast-paced and ever-changing nature of social media—and how consumers use it—the future of social media in marketing might not be merely a continuation of what we have already seen. Therefore, we ask a pertinent question, what is the future of social media in marketing?

Addressing this question is the goal of this article. It is important to consider the future of social media in the context of consumer behavior and marketing, since social media has become a vital marketing and communications channel for businesses, organizations and institutions alike, including those in the political sphere. Moreover, social media is culturally significant since it has become, for many, the primary domain in which they receive vast amounts of information, share content and aspects of their lives with others, and receive information about the world around them (even though that information might be of questionable accuracy). Vitally, social media is always changing. Social media as we know it today is different than even a year ago (let alone a decade ago), and social media a year from now will likely be different than now. This is due to constant innovation taking place on both the technology side (e.g., by the major platforms constantly adding new features and services) and the user/consumer side (e.g., people finding new uses for social media) of social media.

What is social media?

Definitionally, social media can be thought of in a few different ways. In a practical sense, it is a collection of software-based digital technologies—usually presented as apps and websites—that provide users with digital environments in which they can send and receive digital content or information over some type of online social network. In this sense, we can think of social media as the major platforms and their features, such as Facebook, Instagram, and Twitter. We can also in practical terms of social media as another type of digital marketing channel that marketers can use to communicate with consumers through advertising. But we can also think of social media more broadly, seeing it less as digital media and specific technology services, and more as digital places where people conduct significant parts of their lives. From this perspective, it means that social media becomes less about the specific technologies or platforms, and more about what people do in these environments. To date, this has tended to be largely about information sharing, and, in marketing, often thought of as a form of (online) word of mouth (WOM).

Building on these definitional perspectives, and thinking about the future, we consider social media to be a technology-centric—but not entirely technological—ecosystem in which a diverse and complex set of behaviors, interactions, and exchanges involving various kinds of interconnected actors (individuals and firms, organizations, and institutions) can occur. Social media is pervasive, widely used, and culturally relevant. This definitional perspective is deliberately broad because we believe that social media has essentially become almost anything—content, information, behaviors, people, organizations, institutions—that can exist in an interconnected, networked digital environment where interactivity is possible. It has evolved from being simply an online instantiation of WOM behaviors and content/information creation and sharing. It is pervasive across societies (and geographic borders) and culturally prominent at both local and global levels.

Throughout the paper we consider many of the definitional and phenomenological aspects described above and explore their implications for consumers and marketing in order to address our question about the future of marketing-related social media. By drawing on academic research, discussions with industry leaders, popular discourse, and our own expertise, we present and discuss a framework featuring nine themes that we believe will meaningfully shape the future of social media in marketing. These themes by no means represent a comprehensive list of all emerging trends in the social media domain and include aspects that are both familiar in extant social media marketing literature (e.g., online WOM, engagement, and user-generated content) and emergent (e.g., sensory considerations in human-computer interaction and new types of unstructured data, including text, audio, images, and video). The themes we present were chosen because they capture important changes in the social media space through the lenses of important stakeholders, including consumers, industry/practice, and public policy.

In addition to describing the nature and consequences of each theme, we identify research directions that academics and practitioners may wish to explore. While it is infeasible to forecast precisely what the future has in store or to project these on a specific timeline, we have organized the emergent themes into three time-progressive waves, according to imminence of impact (i.e., the immediate, near, and far future). Before presenting our framework for the future of social media in marketing and its implications for research (and practice and policy), we provide a brief overview of where social media currently stands as a major media and marketing channel.

Social media at present

The current social media landscape has two key aspects to it. First are the platforms—major and minor, established and emerging—that provide the underlying technologies and business models making up the industry and ecosystem. Second are the use cases; i.e., how various kinds of people and organizations are using these technologies and for what purposes.

The rise of social media, and the manner in which it has impacted both consumer behavior and marketing practice, has largely been driven by the platforms themselves. Some readers might recall the “early days” of social media where social networking sites such as MySpace and Friendster were popular. These sites were precursors to Facebook and everything else that has developed over the last decade. Alongside these platforms, we continue to have other forms of social media such as messaging (which started with basic Internet Relay Chat services in the 1990s and the SMS text messaging built into early digital mobile telephone standards in the 2000s), and asynchronous online conversations arranged around specific topics of interest (e.g., threaded discussion forums, subreddits on Reddit). More recently, we have seen the rise of social media platforms where images and videos replace text, such as Instagram and Snapchat.

Across platforms, historically and to the present day, the dominant business model has involved monetization of users (audiences) by offering advertising services to anyone wishing to reach those audiences with digital content and marketing communications. Prior research has examined the usefulness of social media (in its various forms) for marketing purposes. For example, work by Trusov et al. ( 2009 ) and Stephen and Galak ( 2012 ) demonstrated that certain kinds of social interactions that now happen on social media (e.g., “refer a friend” features and discussions in online communities) can positively affect important marketing outcomes such as new customer acquisition and sales. More recently, the value of advertising on social media continues to be explored (e.g., Gordon et al. 2019 ), as well as how it interacts with other forms of media such as television (e.g., Fossen and Schweidel 2016 , 2019 ) and affects new product adoption through diffusion of information mechanisms (e.g., Hennig-Thurau et al. 2015 ).

Although the rise (and fall) of various kinds of social media platforms has been important for understanding the social media landscape, our contention is that understanding the current situation of social media, at least from a marketing perspective, lies more in what the users do on these platforms than the technologies or services offered by these platforms. Presently, people around the world use social media in its various forms (e.g., news feeds on Facebook and Twitter, private messaging on WhatsApp and WeChat, and discussion forums on Reddit) for a number of purposes. These can generally be categorized as (1) digitally communicating and socializing with known others, such as family and friends, (2) doing the same but with unknown others but who share common interests, and (3) accessing and contributing to digital content such as news, gossip, and user-generated product reviews.

All of these use cases are essentially WOM in one form or another. This, at least, is how marketing scholars have mainly characterized social media, as discussed by Lamberton and Stephen ( 2016 ). Indeed, online WOM has been—and, we contend, will continue to be—important in marketing (e.g., in the meta-analysis by Babić Rosario et al. 2016 the authors found, on average, a positive correlation between online WOM and sales). The present perspective on social media is that people use it for creating, accessing, and spreading information via WOM to various types of others, be it known “strong ties” or “weak ties” in their networks or unknown “strangers.” Some extant research has looked at social media from the WOM perspective of the consequences of the transmission of WOM (e.g., creating a Facebook post or tweeting) on others (e.g., Herhausen et al. 2019 ; Stephen and Lehmann 2016 ), the impact of the type of WOM content shared on others’ behavior (e.g., Villarroel Ordenes et al. 2017 ; Villarroel Ordenes et al. 2018 ), and on the motivations that drive consumer posting on social media, including considerations of status and self-presentation (e.g., Grewal et al. 2019 ; Hennig-Thurau et al. 2004 ; Hollenbeck and Kaikati 2012 ; Toubia and Stephen 2013 ; Wallace et al. 2014 ).

While this current characterization of WOM appears reasonable, it considers social media only from a communications perspective (and as a type of media channel). However, as social media matures, broader social implications emerge. To appropriately consider the future, we must expand our perspective beyond the narrow communicative aspects of social media and consider instead how consumers might use it. Hence, in our vision for the future of social media in marketing in the following sections, we attempt to present a more expansive perspective of what social media is (and will become) and explain why this perspective is relevant to marketing research and practice.

Overview of framework for the future of social media in marketing

In the following sections we present a framework for the immediate, near, and far future of social media in marketing when considering various relevant stakeholders. Themes in the immediate future represent those which already exist in the current marketplace, and that we believe will continue shaping the social media landscape. The near future section examines trends that have shown early signs of manifesting, and that we believe will meaningfully alter the social media landscape in the imminent future. Finally, themes designated as being in the far future represent more speculative projections that we deem capable of long-term influence on the future of social media. The next sections delve into each of the themes in Table 1 , organized around the predicted imminence of these theme’s importance to marketing (i.e., the immediate, near, and far futures).

The immediate future

To begin our discussion on the direction of social media, in this section, we highlight three themes that have surfaced in the current environment that we believe will continue to shape the social media landscape in the immediate future. These themes—omni-social presence, the rise of influencers, and trust and privacy concerns—reflect the ever-changing digital and social media landscape that we presently face. We believe that these different areas will influence a number of stakeholders such as individual social media users, firms and brands that utilize social media, and public policymakers (e.g., governments, regulators).

Omni-social presence

In its early days, social media activity was mostly confined to designated social media platforms such as Facebook and Twitter (or their now-defunct precursors). However, a proliferation of websites and applications that primarily serve separate purposes have capitalized on the opportunity to embed social media functionality into their interfaces. Similarly, all major mobile and desktop operating systems have in-built social media integration (e.g., sharing functions built into Apple’s iOS). This has made social media pervasive and ubiquitous—and perhaps even omnipotent—and has extended the ecosystem beyond dedicated platforms.

Accordingly, consumers live in a world in which social media intersects with most aspects of their lives through digitally enabled social interactivity in such domains as travel (e.g., TripAdvisor), work (e.g., LinkedIn), food (e.g., Yelp), music (e.g., Spotify), and more. At the same time, traditional social media companies have augmented their platforms to provide a broader array of functionalities and services (e.g., Facebook’s marketplace, Chowdry 2018 ; WeChat’s payment system, Cheng 2017 ). These bidirectional trends suggest that the modern-day consumer is living in an increasingly “omni-social” world.

From a marketing perspective, the “omni-social” nature of the present environment suggests that virtually every part of a consumer’s decision-making process is prone to social media influence. Need recognition might be activated when a consumer watches their favorite beauty influencer trying a new product on YouTube. A consumer shopping for a car might search for information by asking their Facebook friends what models they recommend. A hungry employee might sift through Yelp reviews to evaluate different lunch options. A traveler might use Airbnb to book future accommodation. Finally, a highly dissatisfied (or delighted) airline passenger might rant (rave) about their experience on Twitter. While the decision-making funnel is arguably growing flatter than the aforementioned examples would imply (Cortizo-Burgess 2014 ), these independent scenarios illustrate that social media has the propensity to influence the entire consumer-decision making process, from beginning to end.

Finally, perhaps the greatest indication of an “omni-social” phenomenon is the manner in which social media appears to be shaping culture itself. YouTube influencers are now cultural icons, with their own TV shows (Comm 2016 ) and product lines (McClure 2015 ). Creative content in television and movies is often deliberately designed to be “gifable” and meme-friendly (Bereznak 2018 ). “Made-for-Instagram museums” are encouraging artistic content and experiences that are optimized for selfie-taking and posting (Pardes 2017 ). These examples suggest that social media’s influence is hardly restricted to the “online” world (we discuss the potential obsolescence of this term later in this paper), but is rather consistently shaping cultural artifacts (television, film, the arts) that transcend its traditional boundaries. We believe this trend will continue to manifest, perhaps making the term “social media” itself out-of-date, as it’s omni-presence will be the default assumption for consumers, businesses, and artists in various domains.

This omni-social trend generates many questions to probe in future research. For example, how will social interactivity influence consumer behavior in areas that had traditionally been non-social? From a practitioner lens, it might also be interesting to explore how marketers can strategically address the flatter decision-making funnel that social media has enabled, and to examine how service providers can best alter experiential consumption when anticipating social media sharing behavior.

The rise of new forms of social influence (and influencers)

The idea of using celebrities (in consumer markets) or well-known opinion leaders (in business markets), who have a high social value, to influence others is a well-known marketing strategy (Knoll and Matthes 2017 ). However, the omnipresence of social media has tremendously increased the accessibility and appeal of this approach. For example, Selena Gomez has over 144 million followers on Instagram that she engages with each of her posts. In 2018, the exposure of a single photo shared by her was valued at $3.4 million (Maxim 2018 ). However, she comes at a high price: one post that Selena sponsors for a brand can cost upwards of $800,000 (Mejia 2018 ). However, putting high valuations on mere online exposures or collecting “likes” for specific posts can be somewhat speculative, as academic research shows that acquiring “likes” on social media might have no effect on consumers’ attitudes or behaviors (John et al. 2017 ; Mochon et al. 2017 ). Moreover, Hennig-Thurau et al. ( 2015 ), show that while garnering positive WOM has little to no effect on consumer preferences, negative WOM can have a negative effect on consumer preferences.

While celebrities like Selena Gomez are possible influencers for major brands, these traditional celebrities are so expensive that smaller brands have begun, and will continue to, capitalize on the popularity and success of what are referred to as “micro-influencers,” representing a new form of influencers. Micro-influencers are influencers who are not as well-known as celebrities, but who have strong and enthusiastic followings that are usually more targeted, amounting anywhere between a few thousand to hundreds of thousands of followers (Main 2017 ). In general, these types of influencers are considered to be more trustworthy and authentic than traditional celebrities, which is a major reason influencer marketing has grown increasingly appealing to brands (Enberg 2018 ). These individuals are often seen as credible “experts” in what they post about, encouraging others to want to view the content they create and engage with them. Furthermore, using these influencers allows the brand via first person narration (compared to ads), which is considered warmer and more personal, and was shown to be more effective in engaging consumers (Chang et al. 2019 ).

Considering the possible reach and engagement influencers command on social media, companies have either begun embracing influencers on social media, or plan to expand their efforts in this domain even more. For example, in recent conversations we had with social media executives, several of them stated the growing importance of influencers and mentioned how brands generally are looking to incorporate influencer marketing into their marketing strategies. Further, recent conversations with executives at some globally leading brands suggest that influencer marketing spending by big brands continues to rise.

While influencer marketing on social media is not new, we believe it has a lot of potential to develop further as an industry. In a recent working paper, Duani et al. ( 2018 ) show that consumers enjoy watching a live experience much more and for longer time periods than watching a prerecorded one. Hence, we think live streaming by influencers will continue to grow, in broad domains as well as niche ones. For example, streaming of video game playing on Twitch, a platform owned by Amazon, may still be niche but shows no signs of slowing down. However, live platforms are limited by the fact that the influencers, being human, need to sleep and do other activities offline. Virtual influencers (i.e., “CGI” influencers that look human but are not), on the other hand, have no such limitations. They never get tired or sick, they do not even eat (unless it is needed for a campaign). Some brands have started exploring the use of virtual influencers (Nolan 2018 ), and we believe that in coming years, along with stronger computing power and artificial intelligence algorithms, virtual influencers will become much more prominent on social media, being able to invariably represent and act on brand values and engage with followers anytime.

There are many interesting future research avenues to consider when thinking about the role of influencers on social media. First, determining what traits and qualities (e.g., authenticity, trust, credibility, and likability) make sponsored posts by a traditional celebrity influencer, versus a micro-influencer, or even compared to a CGI influencer, more or less successful is important to determine for marketers. Understanding whether success has to do with the actual influencer’s characteristics, the type of content being posted, whether content is sponsored or not, and so on, are all relevant concerns for companies and social media platforms when determining partnerships and where to invest effort in influencers. In addition, research can focus on understanding the appeal of live influencer content, and how to successfully blend influencer content with more traditional marketing mix approaches.

Privacy concerns on social media

Consumer concerns regarding data privacy, and their ability to trust brands and platforms are not new (for a review on data privacy see Martin and Murphy 2017 ). Research in marketing and related disciplines has examined privacy and trust concerns from multiple angles and using different definitions of privacy. For example, research has focused on the connections between personalization and privacy (e.g., Aguirre et al. 2015 ; White et al. 2008 ), the relationship of privacy as it relates to consumer trust and firm performance (e.g., Martin 2018 ; Martin et al. 2017 ), and the legal and ethical aspects of data and digital privacy (e.g., Culnan and Williams 2009 ; Nill and Aalberts 2014 ). Despite this topic not seeming novel, the way consumers, brands, policy makers, and social media platforms are all adjusting and adapting to these concerns are still in flux and without clear resolution.

Making our understanding of privacy concerns even less straightforward is the fact that, across extant literature, a clear definition of privacy is hard to come by. In one commentary on privacy, Stewart ( 2017 ), defined privacy as “being left alone,” as this allows an individual to determine invasions of privacy. We build from this definition of privacy to speculate on a major issue in privacy and trust moving forward. Specifically, how consumers are adapting and responding to the digital world, where “being left alone” isn’t possible. For example, while research has shown benefits to personalization tactics (e.g., Chung et al. 2016 ), with eroding trust in social platforms and brands that advertise through them, many consumers would rather not share data and privacy for a more personalized experiences, are uncomfortable with their purchases being tracked and think it should be illegal for brands to be able to buy their data (Edelman 2018 ). These recent findings seem to be in conflict with previously established work on consumer privacy expectations. Therefore, understanding if previously studied factors that mitigated the negative effects of personalization (e.g., perceived utility; White et al. 2008 ) are still valued by consumers in an ever-changing digital landscape is essential for future work.

In line with rising privacy concerns, the way consumers view brands and social media is becoming increasingly negative. Consumers are deleting their social media presence, where research has shown that nearly 40% of digitally connected individuals admitted to deleting at least one social media account due to fears of their personal data being mishandled (Edelman 2018 ). This is a negative trend not only for social media platforms, but for the brands and advertisers who have grown dependent on these avenues for reaching consumers. Edelman found that nearly half of the surveyed consumers believed brands to be complicit in negative aspects of content on social media such as hate speech, inappropriate content, or fake news (Edelman 2018 ). Considering that social media has become one of the best places for brands to engage with consumers, build relationships, and provide customer service, it’s not only in the best interest of social media platforms to “do better” in terms of policing content, but the onus of responsibility has been placed on brands to advocate for privacy, trust, and the removal of fake or hateful content.

Therefore, to combat these negative consumer beliefs, changes will need to be made by everyone who benefits from consumer engagement on social media. Social media platforms and brands need to consider three major concerns that are eroding consumer trust: personal information, intellectual property and information security (Information Technology Faculty 2018 ). Considering each of these concerns, specific actions and initiatives need to be taken for greater transparency and subsequent trust. We believe that brands and agencies need to hold social media accountable for their actions regarding consumer data (e.g., GDPR in the European Union) for consumers to feel “safe” and “in control,” two factors shown necessary in cases of privacy concerns (e.g., Tucker 2014 ; Xu et al. 2012 ). As well, brands need to establish transparent policies regarding consumer data in a way that recognizes the laws, advertising restrictions, and a consumer’s right to privacy (a view shared by others; e.g., Martin et al. 2017 ). All of this is managerially essential for brands to engender feelings of trust in the increasingly murky domain of social media.

Future research can be conducted to determine consumer reactions to different types of changes and policies regarding data and privacy. As well, another related and important direction for future research, will be to ascertain the spillover effects of distrust on social media. Specifically, is all content shared on social media seen as less trustworthy if the platform itself is distrusted? Does this extend to brand messages displayed online? Is there a negative spillover effect to other user-generated content shared through these platforms?

The near future

In the previous section, we discussed three areas where we believe social media is immediately in flux. In this section, we identify three trends that have shown early signs of manifesting, and which we believe will meaningfully alter the social media landscape in the near, or not-too-distant, future. Each of these topics impact the stakeholders we mentioned when discussing the immediate social media landscape.

Combatting loneliness and isolation

Social media has made it easier to reach people. When Facebook was founded in 2004, their mission was “to give people the power to build community and bring the world closer together... use Facebook to stay connected with friends and family, to discover what’s going on in the world, and to share and express what matters to them” (Facebook 2019 ). Despite this mission, and the reality that users are more “connected” to other people than ever before, loneliness and isolation are on the rise. Over the last fifty years in the U.S., loneliness and isolation rates have doubled, with Generation Z considered to be the loneliest generation (Cigna 2018 ). Considering these findings with the rise of social media, is the fear that Facebook is interfering with real friendships and ironically spreading the isolation it was designed to conquer something to be considered about (Marche 2012 )?

The role of social media in this “loneliness epidemic” is being hotly debated. Some research has shown that social media negatively impacts consumer well-being. Specifically, heavy social media use has been associated with higher perceived social isolation, loneliness, and depression (Kross et al. 2013 ; Primack et al. 2017 ; Steers et al. 2014 ). Additionally, Facebook use has been shown to be negatively correlated with consumer well-being (Shakya and Christakis 2017 ) and correlational research has shown that limiting social media use to 10 min can decrease feelings of loneliness and depression due to less FOMO (e.g., “fear of missing out;” Hunt et al. 2018 ).

On the other hand, research has shown that social media use alone is not a predictor of loneliness as other factors have to be considered (Cigna 2018 ; Kim et al. 2009 ). In fact, while some research has shown no effect of social media on well-being (Orben et al. 2019 ), other research has shown that social media can benefit individuals through a number of different avenues such as teaching and developing socialization skills, allowing greater communication and access to a greater wealth of resources, and helping with connection and belonging (American Psychological Association 2011 ; Baker and Algorta 2016 ; Marker et al. 2018 ). As well, a working paper by Crolic et al. ( 2019 ) argues that much of the evidence of social media use on consumer well-being is of questionable quality (e.g., small and non-representative samples, reliance on self-reported social media use), and show that some types of social media use are positively associated with psychological well-being over time.

Managerially speaking, companies are beginning to respond as a repercussion of studies highlighting a negative relationship between social media and negative wellbeing. For example, Facebook has created “time limit” tools (mobile operating systems, such as iOS, now also have these time-limiting features). Specifically, users can now check their daily times, set up reminder alerts that pop up when a self-imposed amount of time on the apps is hit, and there is the option to mute notifications for a set period of time (Priday 2018 ). These different features seem well-intentioned and are designed to try and give people a more positive social media experience. Whether these features will be used is unknown.

Future research can address whether or not consumers will use available “timing” tools on one of many devices in which their social media exists (i.e., fake self-policing) or on all of their devices to actually curb behavior. It could also be the case that users will actually spend less time on Facebook and Instagram, but possibly spend that extra time on other competing social media platforms, or attached to devices, which theoretically will not help combat loneliness. Understanding how (and which) consumers use these self-control tools and how impactful they are is a potentially valuable avenue for future research.

One aspect of social media that has yet to be considered in the loneliness discussion through empirical measures, is the quality of use (versus quantity). Facebook ads have begun saying, “The best part of Facebook isn’t on Facebook. It’s when it helps us get together” (Facebook 2019 ). There have been discussions around the authenticity of this type of message, but at its core, in addition to promoting quantity differences, it’s speaking to how consumers use the platform. Possibly, to facilitate this message, social media platforms will find new ways to create friend suggestions between individuals who not only share similar interests and mutual friends to facilitate in-person friendships (e.g., locational data from the mobile app service). Currently there are apps that allow people to search for friends that are physically close (e.g., Bumble Friends), and perhaps social media will go in this same direction to address the loneliness epidemic and stay current.

Future research can examine whether the quantity of use, types of social media platforms, or the way social media is used causally impacts perceived loneliness. Specifically, understanding if the negative correlations found between social media use and well-being are due to the demographics of individuals who use a lot of social media, the way social media works, or the way users choose to engage with the platform will be important for understanding social media’s role (or lack of role) in the loneliness epidemic.

Integrated customer care

Customer care via digital channels as we know it is going to change substantially in the near future. To date, many brands have used social media platforms as a place for providing customer care, addressing customers’ specific questions, and fixing problems. In the future, social media-based customer care is expected to become even more customized, personalized, and ubiquitous. Customers will be able to engage with firms anywhere and anytime, and solutions to customers’ problems will be more accessible and immediate, perhaps even pre-emptive using predictive approaches (i.e., before a customer even notices an issue or has a question pop into their mind).

Even today, we observe the benefits that companies gain from connecting with customers on social media for service- or care-related purposes. Customer care is implemented in dedicated smartphone apps and via direct messaging on social media platforms. However, it appears that firms want to make it even easier for customers to connect with them whenever and wherever they might need. Requiring a customer to download a brand specific app or to search through various social media platforms to connect with firms through the right branded account on a platform can be a cumbersome process. In those cases, customers might instead churn or engage in negative WOM, instead of connecting with the firm to bring up any troubles they might have.

The near future of customer care on social media appears to be more efficient and far-reaching. In a recent review on the future of customer relationship management, Haenlein ( 2017 ) describes “invisible CRM” as future systems that will make customer engagement simple and accessible for customers. New platforms have emerged to make the connection between customer and firm effortless. Much of this is via instant messaging applications for businesses, which several leading technology companies have recently launched as business-related features in existing platforms (e.g., contact business features in Facebook Messenger and WhatsApp or Apple’s Business Chat).

These technologies allow businesses to directly communicate via social media messaging services with their customers. Amazon, Apple, Facebook, and Google are in the process, or have already released early versions of such platforms (Dequier 2018 ). Customers can message a company, ask them questions, or even order products and services through the messaging system, which is often built around chatbots and virtual assistants. This practice is expected to become more widespread, especially because it puts brands and companies into the social media messaging platforms their customers already use to communicate with others, it provides quicker—even instantaneous—responses, is economically scalable through the use of AI-driven chatbots, and, despite the use of chatbots, can provide a more personalized level of customer service.

Another area that companies will greatly improve upon is data collection and analysis. While it is true that data collection on social media is already pervasive today, it is also heavily scrutinized. However, we believe that companies will adapt to the latest regulation changes (e.g., GDPR in Europe, CCPA in California) and improve on collecting and analyzing anonymized data (Kakatkar and Spann 2018 ). Furthermore, even under these new regulations, personalized data collection is still allowed, but severely limits firm’s abilities to exploit consumers’ data, and requires their consent for data collection.

We believe that in the future, companies will be able recognize early indications of problems within customer chatter, behavior, or even physiological data (e.g., monitoring the sensors in our smart watches) before customers themselves even realize they are experiencing a problem. For example, WeWork, the shared workspace company, collects data on how workers move and act in a workspace, building highly personalized workspaces based on trends in the data. Taking this type of approach to customer care will enable “seamless service,” where companies would be able to identify and address consumer problems when they are still small and scattered, and while only a small number of customers are experiencing problems. Customer healthcare is a pioneer in this area, where using twitter and review sites were shown to predict poor healthcare quality (Greaves et al. 2013 ), listen to patients to analyze trending terms (Baktha et al. 2017 ; Padrez et al. 2016 ), or even predict disease outbreaks (Schmidt 2012 ).

Companies, wanting to better understand and mimic human interactions, will invest a lot of R&D efforts into developing better Natural Language Processing, voice and image recognition, emotional analysis, and speech synthesis tools (Sheth 2017 ). For example, Duplex, Google’s latest AI assistant, can already call services on its own and seamlessly book reservations for their users (Welch 2018 ). In the future, AI systems will act as human ability augmenters, allowing us to accomplish more, in less time, and better results (Guszcza 2018 ).

For marketers, this will reduce the need for call centers and agents, reducing points of friction in service and increasing the convenience for customers (Kaplan and Haenlein 2019 ). However, some raise the question that the increased dependence on automation may result in a loss of compassion and empathy. In a recent study, Force (2018) shows that interacting with brands on social media lowered people’s empathy. In response to such concerns, and to educate and incentivize people to interact with machines in a similar way they do with people, Google programmed their AI assistant to respond in a nicer way if you use a polite, rather than a commanding approach (Kumparak 2018 ). While this might help, more research is needed to understand the effect of an AI rich world on human behavior. As well, future research can examine how consumer generated data can help companies preemptively predict consumer distress. Another interesting path for research would be to better understand the difference in consumer engagement between the various platforms, and the long-term effects of service communications with non-human AI and IoT.

Social media as a political tool

Social media is a platform to share thoughts and opinions. This is especially true in the case of disseminating political sentiments. Famously, President Barack Obama’s victory in the 2008 election was partially attributed to his ability to drive and engage voters on social media (Carr 2008 ). Indeed, Bond et al. ( 2012 ) have shown that with simple interventions, social media platforms can increase targeted audiences’ likelihood of voting. Social media is considered one of the major drivers of the 2010 wave of revolutions in Arab countries, also known as the Arab Spring (Brown et al. 2012 ).

While social media is not new to politics, we believe that social media is transitioning to take a much larger role as a political tool in the intermediate future. First evidence for this could be seen in the 2016 U.S. presidential election, as social media took on a different shape, with many purported attempts to influence voter’s opinions, thoughts, and actions. This is especially true for then-candidate and now-President Donald Trump. His use of Twitter attracted a lot of attention during the campaign and has continued to do so during his term in office. Yet, he is not alone, and many politicians changed the way they work and interact with constituents, with a recent example of Congresswoman Alexandria Ocasio-Cortez that even ran a workshop for fellow congress members on social media (Dwyer 2019 ).

While such platforms allow for a rapid dissemination of ideas and concepts (Bonilla and Rosa 2015 ; Bode 2016 ), there are some, both in academia and industry that have raised ethical concerns about using social media for political purposes. Given that people choose who to follow, this selective behavior is said to potentially create echo chambers, wherein, users are exposed only to ideas by like-minded people, exhibiting increased political homophily (Bakshy et al. 2015 ). People’s preference to group with like-minded people is not new. Social in-groups have been shown to promote social identification and promote in-group members to conform to similar ideas (Castano et al. 2002 ; Harton and Bourgeois 2004 ). Furthermore, it was also shown that group members strongly disassociate and distance themselves from outgroup members (Berger and Heath 2008 ; White and Dahl 2007 ). Thus, it is not surprising to find that customized newsfeeds within social media exacerbate this problem by generating news coverage that is unique to specific users, locking them in their purported echo chambers (Oremus 2016 ).

While social media platforms admit that echo chambers could pose a problem, a solution is not clear (Fiegerman 2018 ). One reason that echo chambers present such a problem, is their proneness to fake news. Fake news are fabricated stories that try to disguise themselves as authentic content, in order to affect other social media users. Fake news was widely used in the 2016 U.S. elections, with accusations that foreign governments, such as Iran and Russia, were using bots (i.e., online automatic algorithms), to spread falsified content attacking Hillary Clinton and supporting President Trump (Kelly et al. 2018 ). Recent research has furthermore shown how the Chinese government strategically uses millions of online comments to distract the Chinese public from discussing sensitive issues and promote nationalism (King et al. 2017 ). In their latest incarnation, fake news uses an advanced AI technique called “Deep Fake” to generate ultra-realistic forged images and videos of political leaders while manipulating what those leaders say (Schwartz 2018 ). Such methods can easily fool even the sharpest viewer. In response, research has begun to explore ways that social media platforms can combat fake news through algorithms that determine the quality of shared content (e.g., Pennycook and Rand 2019 ).

One factor that has helped the rise of fake news is echo chambers. This occurs as the repeated sharing of fake news by group members enhance familiarity and support (Schwarz and Newman 2017 ). Repetition of such articles by bots can only increase that effect. Recent research has shown that in a perceived social setting, such as social media, participants were less likely to fact-check information (Jun et al. 2017 ), and avoided information that didn’t fit well with their intuition (Woolley and Risen 2018 ). Schwarz and Newman ( 2017 ) state that misinformation might be difficult to correct, especially if the correction is not issued immediately and the fake news has already settled into the minds of users. It was also shown that even a single exposure to fake news can create long term effect on users, making their effect larger than previously thought (Pennycook et al. 2019 ).

Notably, some research has found that exposure to opposing views (i.e., removing online echo chambers) may in fact increase (versus decrease) polarization (Bail et al. 2018 ). Accordingly, more work from policy makers, businesses, and academics is needed to understand and potentially combat political extremism. For example, policy makers and social media platforms will continually be challenged to fight “fake news” without censoring free speech. Accordingly, research that weighs the risk of limited freedom of expression versus the harms of spreading fake news would yield both theoretical and practically meaningful insights.

The far future

In this section, we highlight three emerging trends we believe will have a have long-term influence on the future of social media. Note that although we label these trends as being in the “far” future, many of the issues described here are already present or emerging. However, they represent more complex issues that we believe will take longer to address and be of mainstream importance for marketing than the six issues discussed previously under the immediate and near futures.

Increased sensory richness

In its early days, the majority of social media posts (e.g., on Facebook, Twitter) were text. Soon, these platforms allowed for the posting of pictures and then videos, and separate platforms dedicated themselves to focus on these specific forms of media (e.g., Instagram and Pinterest for pictures, Instagram and SnapChat for short videos). These shifts have had demonstrable consequences on social media usage and its consequences as some scholars suggest that image-based posts convey greater social presence than text alone (e.g., Pittman and Reich 2016 ). Importantly however, a plethora of new technologies in the market suggest that the future of social media will be more sensory-rich.

One notable technology that has already started infiltrating social media is augmented reality (AR). Perhaps the most recognizable examples of this are Snapchat’s filters, which use a device’s camera to superimpose real-time visual and/or video overlays on people’s faces (including features such as makeup, dog ears, etc.). The company has even launched filters to specifically be used on users’ cats (Ritschel 2018 ). Other social media players quickly joined the AR bandwagon, including Instagram’s recent adoption of AR filters (Rao 2017 ) and Apple’s Memoji messaging (Tillman 2018 ). This likely represents only the tip of the iceberg, particularly given that Facebook, one of the industry’s largest investors in AR technology, has confirmed it is working on AR glasses (Constine 2018 ). Notably, the company plans to launch a developer platform, so that people can build augmented-reality features that live inside Facebook, Instagram, Messenger and Whatsapp (Wagner 2017 ). These developments are supported by academic research suggesting that AR often provides more authentic (and hence positive) situated experiences (Hilken et al. 2017 ). Accordingly, whether viewed through glasses or through traditional mobile and tablet devices, the future of social media is likely to look much more visually augmented.

While AR allows users to interact within their current environments, virtual reality (VR) immerses the user in other places, and this technology is also likely to increasingly permeate social media interactions. While the Facebook-owned company Oculus VR has mostly been focusing on the areas of immersive gaming and film, the company recently announced the launch of Oculus Rooms where users can spend time with other users in a virtual world (playing games together, watching media together, or just chatting; Wagner 2018 ). Concurrently, Facebook Spaces allows friends to meet online in virtual reality and similarly engage with one another, with the added ability to share content (e.g., photos) from their Facebook profiles (Whigham 2018 ). In both cases, avatars are customized to represent users within the VR-created space. As VR technology is becoming more affordable and mainstream (Colville 2018 ) we believe social media will inevitably play a role in the technology’s increasing usage.

While AR and VR technologies bring visual richness, other developments suggest that the future of social media might also be more audible. A new player to the social media space, HearMeOut, recently introduced a platform that enables users to share and listen to 42-s audio posts (Perry 2018 ). Allowing users to use social media in a hands-free and eyes-free manner not only allows them to safely interact with social media when multitasking (particularly when driving), but voice is also said to add a certain richness and authenticity that is often missing from mere text-based posts (Katai 2018 ). Given that podcasts are more popular than ever before (Bhaskar 2018 ) and voice-based search queries are the fastest-growing mobile search type (Robbio 2018 ), it seems likely that this communication modality will accordingly show up more on social media use going forward.

Finally, there are early indications that social media might literally feel different in the future. As mobile phones are held in one’s hands and wearable technology is strapped onto one’s skin, companies and brands are exploring opportunities to communicate to users through touch. Indeed, haptic feedback (technology that recreates the sense of touch by applying forces, vibrations, or motions to the user; Brave et al. 2001 ) is increasingly being integrated into interfaces and applications, with purposes that go beyond mere call or message notifications. For example, some companies are experimenting with integrating haptics into media content (e.g., in mobile ads for Stoli vodka, users feel their phone shake as a woman shakes a cocktail; Johnson 2015 ), mobile games, and interpersonal chat (e.g., an app called Mumble! translates text messages into haptic outputs; Ozcivelek 2015 ). Given the high levels of investment into haptic technology (it is predicted to be a $20 billion industry by 2022; Magnarelli 2018 ) and the communicative benefits that stem from haptic engagement (Haans and IJsselsteijn 2006 ), we believe it is only a matter of time before this modality is integrated into social media platforms.

Future research might explore how any of the new sensory formats mentioned above might alter the nature of content creation and consumption. Substantively-focused researchers might also investigate how practitioners can use these tools to enhance their offerings and augment their interactions with customers. It is also interesting to consider how such sensory-rich formats can be used to bridge the gap between the online and offline spaces, which is the next theme we explore.

Online/offline integration and complete convergence

A discussion occurring across industry and academia is on how marketers can appropriately integrate online and offline efforts (i.e., an omnichannel approach). Reports from industry sources have shown that consumers respond better to integrated marketing campaigns (e.g., a 73% boost over standard email campaigns; Safko 2010 ). In academia meanwhile, the majority of research considering online promotions and advertisements has typically focused on how consumers respond to these strategies through online only measures (e.g., Manchanda et al. 2006 ), though this has begun to change in recent years with more research examining offline consequences to omnichannel strategies (Lobschat et al. 2017 ; Kumar et al. 2017 ).

Considering the interest in integrated marketing strategies over the last few years, numerous strategies have been utilized to follow online and offline promotions and their impacts on behavior such as the usage of hashtags to bring conversations online, call-to-actions, utilizing matching strategies on “traditional” avenues like television with social media. While there is currently online/offline integration strategies in marketing, we believe the future will go even further in blurring the lines between what is offline and online to not just increase the effectiveness of marketing promotions, but to completely change the way customers and companies interact with one another, and the way social media influences consumer behavior not only online, but offline.

For brands, there are a number of possible trends in omnichannel marketing that are pertinent. As mentioned earlier, a notable technology that has begun infiltrating social media is augmented reality (AR). In addition to what already exists (e.g., Snapchat’s filters, Pokémon Go), the future holds even more possibilities. For example, Ikea has been working to create an AR app that allows users to take photos of a space at home to exactly , down to the millimeter size and lighting in the room, showcase what a piece of furniture would look like in a consumer’s home (Lovejoy 2017 ). Another set of examples of AR comes from beauty company L’Oréal. In 2014 for the flagship L’Oréal Paris brand they released a mobile app called Makeup Genius that allowed consumers to virtually try on makeup on their phones (Stephen and Brooks 2018 ). Since then, they have developed AR apps for hair color and nail polish, as well as integrating AR into mobile ecommerce webpages for their luxury beauty brand Lancôme. AR-based digital services such as these are likely to be at the heart of the next stage of offline/online integration.

AR, and similar technology, will likely move above and beyond being a tool to help consumers make better decisions about their purchases. Conceivably, similar to promotions that currently exist to excitse consumers and create communities, AR will be incorporated into promotions that integrate offline and online actions. For example, contests on social media will advance to the stage where users get to vote on the best use of AR technology in conjunction with a brand’s products (e.g., instead of users submitting pictures of their apartments to show why they should win free furniture, they could use AR to show how they would lay out the furniture if they were to win it from IKEA).

Another way that the future of online/offline integration on social media needs to be discussed is in the sense of a digital self. Drawing on the extended self in the digital age (Belk 2013 ), the way consumers consider online actions as relevant to their offline selves may be changing. For example, Belk ( 2013 ) spoke of how consumers may be re-embodied through avatars they create to represent themselves online, influencing their offline selves and creating a multiplicity of selves (i.e., consumers have more choice when it comes to their self-representation). As research has shown how digital and social media can be used for self-presentation, affiliation, and expression (Back et al. 2010 ; Gosling et al. 2007 ; Toubia and Stephen 2013 ; Wilcox and Stephen 2012 ), what does it mean for the future if consumers can create who they want to be?

In addition, when considering digital selves, what does this mean for how consumers engage with brands and products? Currently, social media practice is one where brands encourage consumer engagement online (Chae et al. 2017 ; Godes and Mayzlin 2009 ), yet the implications for how these types of actions on the part of the brand to integrate online social media actions and real-life behavior play out are unclear. Research has begun to delve into the individual-level consequences of a consumer’s social media actions on marketing relevant outcomes (Grewal et al. 2019 ; John et al. 2017 ; Mochon et al. 2017 ; Zhang et al. 2017 ), however much is still unknown. As well, while there is recent work examining how the device used to create and view content online impacts consumer perceptions and behaviors (e.g., Grewal and Stephen 2019 ), to date research has not examined these questions in the context of social media. Therefore, future research could address how digital selves (both those held offline and those that only exist online), social media actions, and if the way consumers reach and use various platforms (i.e., device type, app vs. webpage, etc.) impact consumer behavior, interpersonal relationships, and brand-related measures (e.g., well-being, loyalty, purchase behaviors).

Social media by non-humans

The buzz surrounding AI has not escaped social media. Indeed, social bots (computer algorithms that automatically produce content and interact with social media users; Ferrara et al. 2016 ) have inhabited social media platforms for the last decade (Lee et al. 2011 ), and have become increasingly pervasive. For example, experts estimate that up to 15% of active Twitter accounts are bots (Varol et al. 2017 ), and that percentage appears to be on the rise (Romano 2018 ). While academics and practitioners are highly concerned with bot detection (Knight 2018 ), in the vast majority of current cases, users do not appear to recognize when they are interacting with bots (as opposed to other human users) on social media (Stocking and Sumida 2018 ). While some of these bots are said to be benign, and even useful (e.g., acting as information aggregators), they have also been shown to disrupt political discourse (as mentioned earlier), steal personal information, and spread misinformation (Ferrara et al. 2016 ).

Of course, social bots are not only a problem for social media users but are also a nagging concern plaguing marketers. Given that companies often assess marketing success on social media through metrics like Likes, Shares, and Clicks, the existence of bots poses a growing threat to accurate marketing metrics and methods for ROI estimation, such as attribution modelling (Bilton 2014 ). Similarly, when these bots act as “fake followers,” it can inflate the worth of influencers’ audiences (Bogost 2018 ). This can also be used nefariously by individuals and firms, as shown in a New York Times Magazine expose that documented the market used by some influencers to purchase such “fake” followers to inflate their social media reach (Confessore et al. 2018 ). As discussed above in relation to influencer marketing, where it has been commonplace for influencers to be paid for posts at rates proportionate to their follower counts, there have been perverse incentives to game the system by having non-human “fake” bot followers. This, however, erodes consumer trust in the social media ecosystem, which is a growing issue and a near-term problem for many firms using social media channels for marketing purposes.

However, there are instances when consumers do know they are interacting with bots, and do not seem to mind. For example, a number of virtual influencers (created with CGI, as mentioned earlier) seem to be garnering sizeable audiences, despite the fact they are clearly non-human (Walker 2018 ). One of the most popular of these virtual influencers, Lil Miquela, has over 1.5 million followers on Instagram despite openly confessing, “I am not a human being... I’m a robot” (Yurieff 2018 ). Future research might try to understand the underlying appeal of these virtual influencers, and the potential boundary conditions of their success.

Another category of social bots gaining increasing attention are therapy bots. These applications (e.g., “Woebot;” Molteni 2017 ) aim to support the mental health of users by proactively checking in on them, “listening” and chatting to users at any time and recommending activities to improve users’ wellbeing (de Jesus 2018 ). Similar bots are being used to “coach” users, and help them quit maladaptive behaviors, like smoking (e.g., QuitGenius; Crook 2018 ). Interestingly, by being explicitly non-human, these agents are perceived to be less judgmental, and might accordingly be easier for users to confide in.

Finally, the Internet of Things revolution has ushered in with it the opportunity for a number of tangible products and interfaces to “communicate” via social media. For example, in what started as a design experiment, “Brad,” a connected toaster, was given the ability to “communicate” with other connected toasters, and to tweet his “feelings” when neglected or under-used (Vanhemert 2014 ). While this experiment was deliberately designed to raise questions about the future of consumer-product relationships (and product-product “relationships”), the proliferation of autonomous tangible devices does suggest a future in which they have a “voice,” even in the absence of humans (Hoffman and Novak 2018 ).

Going forward, we believe the presence of bots on social media will be more normalized, but also more regulated (e.g., a recent law passed in California prevents bots from masquerading as humans; Smith 2018 ). Further, consumers and companies alike will be become increasingly interested in how bots communicate and interact with each other outside of human involvement. This brings up interesting potential research questions for academics and practitioners alike. How will the presence of non-humans change the nature of content creation and conversation in social media? And how should companies best account for the presence of non-humans in their attribution models?

Future research directions and conclusion

This article has presented nine themes pertinent to the future of social media as it relates to (and is perhaps influenced by) marketing. The themes have implications for individuals/consumers, businesses and organizations, and also public policymakers and governments. These themes, which represent our own thinking and a synthesis of views from extant research, industry experts, and popular public discourse, are of course not the full story of what the future of social media will entail. They are, however, a set of important issues that we believe will be worth considering in both academic research and marketing practice.

To stimulate future research on these themes and related topics, we present a summary of suggested research directions in Table 2 . These are organized around our nine themes and capture many of the suggested research directions mentioned earlier. As a sub-field within the field of marketing, social media is already substantial and the potential for future research—based on identified needs for new knowledge and answers to perplexing questions—suggests that this sub-field will become even more important over time. We encourage researchers to consider the kinds of research directions in Table 2 as examples of issues they could explore further. We also encourage researchers in marketing to treat social media as a place where interesting (and often very new) consumer behaviors exist and can be studied. As we discussed earlier in the paper, social media as a set of platform businesses and technologies is interesting, but it is how people use social media and the associated technologies that is ultimately of interest to marketing academics and practitioners. Thus, we urge scholars to not be overly enticed by the technological “shiny new toys” at the expense of considering the behaviors associated with those technologies and platforms.

Finally, while we relied heavily (though not exclusively) on North American examples to illustrate the emergent themes, there are likely interesting insights to be drawn by explicitly exploring cross-cultural differences in social media usage. For example, variations in regulatory policies (e.g., GDPR in the European Union) may lead to meaningful differences in how trust and privacy concerns manifest. Further, social media as a political tool might be more influential in regions where the mainstream media is notoriously government controlled and censored (e.g., as was the case in many of the Arab Spring countries). While such cross-cultural variation is outside the scope of this particular paper, we believe it represents an area of future research with great theoretical and practical value.

In reviewing the social media ecosystem and considering where it is heading in the context of consumers and marketing practice, we have concluded that this is an area that is very much still in a state of flux. The future of social media in marketing is exciting, but also uncertain. If nothing else, it is vitally important that we better understand social media since it has become highly culturally relevant, a dominant form of communication and expression, a major media type used by companies for advertising and other forms of communication, and even has geopolitical ramifications. We hope that the ideas discussed here stimulate many new ideas and research, which we ultimately hope to see being mentioned and shared across every type of social media platform.

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The authors thank the special issue editors and reviewers for their comments, and the Oxford Future of Marketing Initiative for supporting this research. The authors contributed equally and are listed in alphabetical order or, if preferred, order of Marvel superhero fandom from highest to lowest and order of Bon Jovi fandom from lowest to highest.

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Appel, G., Grewal, L., Hadi, R. et al. The future of social media in marketing. J. of the Acad. Mark. Sci. 48 , 79–95 (2020). https://doi.org/10.1007/s11747-019-00695-1

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Table of Contents

Why people share information, top 7 impacts of social media, top 20+ advantages and disadvantages of social media, the bottom line, social media: advantages and disadvantages | simplilearn.

Information and communication technology has changed rapidly over the past 20 years, with a key development being the  emergence of social media .

The pace of change is accelerating. For example, the development of mobile technology has played an essential role in shaping the impact of social media. Across the globe, mobile devices dominate in terms of total minutes spent online. They put the means to connect anywhere, at any time on any device in everyone’s hands.

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A fascinating study by the New York Times Consumer Insight Group revealed the motivations that participants cited for sharing information on social media. These include a desire to reveal  valuable and entertaining content  to others; to define themselves; to grow and nourish relationships and to get the word out about brands and causes they like or support.

These factors have caused social networks to evolve from being a handy means for keeping in touch with friends and family to being used in ways that have a real impact on society.

The Influence of Social media is being used in ways that shape politics, business, world culture, education, careers, innovation, and more.

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1. The Impact of Social Media on Politics

A new study from Pew Research claims that about one in five U.S. adults gets their political news primarily through social media. The study also finds that those who do get their political news primarily through social media tend to be less well-informed and more likely to be exposed to unproven claims that people who get their news from traditional sources.

In comparison to other media, the influence of social media in political campaigns has increased tremendously. Social networks play an increasingly important role in electoral politics — first in the ultimately unsuccessful candidacy of Howard Dean in 2003, then in the election of the first African-American president in 2008, and again in the Twitter-driven campaign of Donald Trump.

The  New York Times reports  that “The election of Donald J. Trump is perhaps the starkest illustration yet that across the planet, social networks are helping to fundamentally rewire human society.” Because social media allows people to communicate more freely, they are helping to create surprisingly influential social organizations among once-marginalized groups.

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2. The Impact of Social Media on Society

Almost a quarter of the world’s population is now on Facebook. In the U.S., nearly 80% of all internet users are on this platform. Because social networks feed off interactions among people, they become more powerful as they grow.

Thanks to the internet, each person with marginal views can see that he’s not alone. And when these people find one another via social media, they can do things — create memes, publications, and entire online worlds that bolster their worldview, and then break into the mainstream.

Without social media, social, ethical, environmental, and political ills would have minimal visibility. Increased visibility of issues has shifted the balance of power from the hands of a few to the masses.

The flipside: Social media is slowly killing real activism and replacing it with ‘slacktivism’

While social media activism brings an increased awareness about societal issues, questions remain as to whether this awareness is translating into real change. Some argue that social sharing has encouraged people to use computers and mobile phones to express their concerns on social issues without actually having to engage actively with campaigns in real life. Their support is limited to pressing the ‘Like’ button or sharing content.

This passivity is a very human reaction when people are given options that absolve them from the responsibility to act. A  2013 study by the University of British Columbia’s Sauder School of Business  found that when people are presented with the  option of ‘liking’ a social cause , they use this to opt-out of actually committing time and money to a charitable cause. On the other hand, when people are allowed to show support in private, they are more likely to offer meaningful support by making a financial contribution.

The researchers found that a public endorsement is meant to satisfy others’ opinions, whereas people who give in private do so because the cause is aligned to their values. This peer pressure may be a factor in the recent trend of political polls in the U.S. to misread voter intentions: people who respond to the polls may be answering how they think the pollsters expect or the way they think will please their peers, but in the privacy of the voting booth (or at home with a mail-in ballot), they vote according to their true preferences.

3. The Impact of Social Media on Commerce

The rise of social media means it’s unusual to find an organization that does not reach its customers and prospects through one social media platform or another. Companies see the importance of using social media to connect with customers and build revenue.

Businesses have realized they can use social media to generate insights, stimulate demand, and create targeted product offerings. These functions are important in traditional brick-and-motor businesses and, obviously, in the world of e-commerce.

[Related reading:  9 Social Media Marketing Skills You Need Right Now ]

Many studies suggest implementing social networks within the workplace can strengthen knowledge sharing. The result is to improve project management activities and enable the spread of specialized knowledge. Fully implementing social technologies in the workplace removes boundaries, eliminates silos, and can raise interaction and help create more highly skilled and knowledgeable workers.

The flipside: A low number of social ‘shares’ can lead to negative social proof and destroy business credibility

Interestingly, although social sharing has become the norm rather than the exception in business, some companies, after experiencing first-hand some adverse effects of social media, have decided to go against the grain and remove the social sharing buttons from their websites.

A case study of Taloon.com , an e-commerce retailer from Finland, found that conversions rose by 11.9% when they removed share buttons from their product pages.

These results highlight the double-edged nature of the impact of social media. When products attract a lot of shares, it can reinforce sales. But when the reverse is true, customers begin to distrust the product and the company. This effect is what Dr. Paul Marsden, psychologist and author of ‘The Social Commerce Handbook,’ referred to as ‘social proof.’

4. The Impact of Social Media on the World of Work

Social media has had a profound effect on recruitment and hiring. Professional social networks such as LinkedIn are important social media platforms for anyone looking to stand out in their profession. They allow people to create and market a personal brand.

Nineteen percent of hiring managers make their hiring decisions based on information found on social media. According to CareerBuilder's 2018 social media recruitment survey , 70 percent of employers use social networking sites to research job candidates.

Also Read: Personal Branding Vs. Business Branding

5. The Impact of Social Media on Training and Development

Job candidates who develop skills in the latest and most advanced social media techniques are far more employable.

A 2020 survey by OnePoll on behalf of Pearson and Connections Academy asked 2,000 U.S. parents and their high-school aged children about the “new normal” of high school. Sixty-eight percent of students and 65% of their parents believe that social media will be a useful tool and part of the new high school normal.

Blogs , wikis, LinkedIn, Twitter, Facebook , and podcasts are now common tools for learning in many educational institutions. Social media has contributed to the increase in long-distance online learning.

Despite issues of lack of privacy and some instances of cheating among long-distance learners, this has not deterred social platforms from being used in education.

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6. N egative Impact of Social Media

Social Media is relatively a newer technology, hence, it is a little difficult to establish its long-term good and bad consequences. However, multiple researchers have concluded a strong relationship between heavy use of social media platforms with an increase in risk of depression, self-harm, anxiety, and loneliness. 

Fear of Missing Out (FOMO)

Long-use of social media platforms make you addicted to checking out what other people are doing. FOMO is an exacerbated feeling that other people are living better lives or having more fun compared with you. This feeling makes you check your notification every second, just to make yourself feel better. 

Cyberbullying

Teenagers need to fit in, to be popular, and to outdo others. This process was challenging long before the advent of social media. Add Facebook, Twitter, Snapchat, and Instagram into the mix, and you suddenly have teenagers subjected to feeling pressure to grow up too fast in an online world.

The Cyberbullying Institute’s 2019 survey of U.S. middle and high school students found that over 36 percent report having been cyberbullied at some point in their life, with 30 percent having been victimized twice or more. It also found that almost 15 percent admitted to having cyberbullied someone at least once, and nearly 11 percent admitting to doing it two or more times. Teenagers can misuse social media platforms to spread rumors, share videos aimed at destroying reputations, and to blackmail others.

Lack of Privacy

Stalking, identity theft, personal attacks, and misuse of information are some of the threats faced by social media users. Most of the time, the users themselves are to blame as they share content that should not be in the public eye. The confusion arises from a lack of understanding of how the private and public elements of an online profile actually work.

Unfortunately, by the time private content is deleted, it’s usually too late. and the content can cause problems in people’s personal and professional lives.

7. The Impact of Social Media on Relationships

One of the effects of social media is encouraging people to form and cherish "social media friendships" over actual friendships. The term 'friend' as used on social media is a weak shadow of traditional friendship. Real friends actually know each other, frequently interact face to face, and have a personal bond.

If the internet is an unmissable part of contemporary life, social media is integral for communication – an unavoidable element, especially for those who lead hectic lifestyles and depend on it for even the smallest updates. People can communicate with friends, speak with family, and stay updated on global happenings via numerous platforms. One of the most common online activities is using social media, and in 2021, 82% of Americans had a profile on one or more social networking sites, up 2% from the usage rate of 80% the year before. That comes to about 223 million social media users in the United States in 2020.

Over the past ten years, social media has grown astronomically. There was minimal participation in the industry in 2005. At the time, most of them were unaware, and among those who knew, having the opportunity to establish a MySpace page typically meant elaborate backgrounds and unique playlists rather than a direct connection. If people were to spring back a little bit, the real taste of social media emerged from blogging, where accounts were created sometime in the 1980s. After that, the evolution of free platforms and chat rooms created newer social opportunities. Later Facebook, Twitter, and others revolutionized it.

Advantages of Social Media

Connectivity.

Connectivity is among the most significant benefits of social media. It can link countless users at any time, everywhere. Information could be spread globally through social media and its connectedness, making it simple for people to interact with one another. It results in global relationships.

The use of social media in education is commendable. Learners and educators can enroll in global collaborative platforms to facilitate constructive learning. It also aids in skill improvement by fostering knowledge and creativity. 

Information and Updates

Stay informed about events happening across the globe or in other people's lives using social media. In contrast to television, radio, or newspapers, social media lets everyone convey information accurately by presenting the real picture. It aids in showcasing real-world news across the globe.

People have become more conscious thanks to social media. It serves as a channel for information, thus paving the way to innovation and success via developing their knowledge and abilities. Social media well-covers global events, making people more aware of their surroundings.

Share Anything With Others

Social media is the best platform to convey feelings and opinions - a song, a poem, a work of art, a decadent dessert, or anything else. Anyone can let their creativity shine through the platform for it to be shared by millions of others. Sharing the artistic works with others could open the door to achievement and several milestones.

Helps in Building Communities

Live in a diverse world where individuals from different cultures, beliefs, and backgrounds exist. Social media brings these people together by linking them on a common platform. Thus, fostering a sense of unity facilitates the development of community links. For instance, food lovers can join the community of food bloggers, while gamers can join communities focused on gaming, etc.

Noble Cause

Noble deeds can be promoted on social media. It is the ideal tool for endorsing causes like giving donations to those with cancer, for instance, to those who need money for treatment. While everyone can use social media to assist others in finance, it is also the simplest and fastest way to advance any worthwhile cause.

Mental Health

Social media serves as an excellent stress reliever. Several groups can support people battling against stress, depression, and loneliness. By creating a feeling of elation, these communities can bestow a brighter attitude while also helping develop healthy relationships with others, thus enhancing mental health. 

Brand Reputation

Social media improves company relationships by fostering goodwill among users; its promotion increases sales, which in turn increases profitability. The comments and feedback left by customers are a fantastic resource for businesses. Due to the user likes garnered, companies can experience enhanced popularity and a boost in revenue.

Brand Awareness

Networking platforms contribute to greater brand recognition. Visually appealing products and information capture users' attention, which increases brand visibility and raises customer knowledge about certain goods and services.

Customer Interaction

Social media enhances customer engagement by providing goods and services and soliciting comments on them. Users from across communities leave various feedback and suggestions, which can assist in improving areas of focus and satisfy them.

Social media is a great supporter of internet commerce and marketing. Posts and promotions facilitate effective user connections and contribute to the profitability of a business. It fosters user relationships and endorses customer loyalty, which is crucial for any company's expansion.

Disadvantages of Social Media

Affects social-emotional connection.

Social media hampers emotional bonds. Everything is conveyed through texts digitally, which can stunt expressions. Ingenuity is lost when people who would ideally visit one another to convey greetings only send text messages instead of hugs.

Decreases Quick-witted Skill

With the decrease in real face-to-face conversations and in-person chats, quick-wittedness is rare. Sense of humor and sporty tête-à-têtes have been compromised – the sense of love, friendship, fun, and enjoyment have all disappeared due to the effects of social media on human mental health.

Causing Distress to Someone's Feelings

People who use social media to communicate lack empathy and do not wink an eyelid when they have to hurt someone. The latest trolls, negative comments, and feedback are all witnesses to the hard-heartedness that has evolved due to the invisible nature of social media.

Present Physically Not Mentally

Spending time with each other is about being 'present' and in the moment. As friends and family gather, create memories by speaking to one another about times past, present and future. Unfortunately, today with social media being made available on the mobile phone, people spend time with each other 'scrolling' through posts.

Lacking Understanding and Thoughtfulness

Feelings are conveyed through word and voice – but to do this, there is a need to be physically present in front of the other person to communicate feelings effectively. However, social media gives it a different hue when anyone puts them into a text, thus masking the real meaning.

Lack of Quality Family Time

Social media has been the cause of many disrupted relationships simply because families cannot spend quality time with each other. Family time has taken a hit with 'me' and privacy taking precedence (due to the quality of texts that appear on social media).

People, particularly children, have been victims of cyberbullying where threats, cons, and other negative activities easily ensnare them. Fake news and rumors spread effortlessly, leading to depression and suicide.

The vulnerability of social media has also thrown light on how easy it is to gather a person's data. Privacy settings must be constantly updated and profile locked to avoid such situations.

Distracted Mind

Social media is impulsive. New messages, notifications, and updates are the impetus to constantly checking the phone, resulting in distraction. The individual wastes time even ignoring important work to only look at the menial update.

Facilitates Laziness

Spending hours on the couch glued to our smartphones results in several health problems such as obesity, stress, and high blood pressure. Technology and accompanying social media have led to a rise in laziness among people due to no physical activity or exercise.

A serious issue among youth social media addiction has led to disastrous consequences. While checking social media and using the smartphone in moderation is not bad, productive time and energy are wasted due to overuse.

Cheating and Relationship Issues

Individuals are now using social media as a platform for dating and marriage. However, chances are that the information provided on the profile is false, eventually leading to a toxic relationship or even divorce.

It’s been said that information is power. Without a means of distributing information, people cannot harness its power. One positive impact of social media is in the distribution of information in today’s world. Platforms such as Facebook, LinkedIn, Twitter, and others have made it possible to access information at the click of a button.

Research conducted by parse.ly  shows that the life expectancy of a story posted on the web is 2.6 days, compared to 3.2 days when a story is shared on social media. That’s a difference of 23%, which is significant when you consider that billions of people use the internet daily.

The lifespan of an article is different from the active lifespan of a social media post itself. Green Umbrella estimates that a Facebook post has an average lifespan of 6 hours, an Instagram post or LinkedIn post of 48 hours, and a tweet on Twitter a mere 18 minutes. The longer social media users actively access the information, the more discussion it generates and the greater the social media impact. The shorter the active lifespan, the more frequently one must post to that channel to maintain engagement (recognizing that posting too frequently can cause reader burnout).

While the world would be a much slower place without social media, it’s caused harm as well as good. However, the positive impact of social media is astronomical and far surpasses the ills associated with sharing.

Ultimately, sharing is about getting people to see and respond to content. As long as the content is still relevant and the need for information still exists, it’s always worthwhile for any organization to use social media to keep publishing.

Q1. What is the main impact of social media on society?

Social media has changed the way we live our lives. It has redefined the way we imagine our surroundings. Who could have imagined that community networking sites would become a major platform for brands to find potential customers! There are both positive and negative impacts of social media on society as well as businesses. 

Q2.What is the impact of social media in our daily lives?

Social media can impact you both positively and negatively. If you are a brand manager, or small business owner, then social media is a great platform for you to meet your customers. However, for individuals, social media is more like an addiction which may cause discomfort if not addressed properly. 

Q3. What is the impact of social media in the modern world? 

Social media in the modern world is used to connect with your friends and see what they are up-to without even calling them. It provides us a comfortable solution to connecting with our dear ones. For brands and businesses, social media is more like an advertising platform. 

Q4. What are the five main benefits of social media? 

Social media is a great innovation that has changed the way we communicate and interact with each other. Here are 5 main benefits of social media - 

• Stay updated with all the new things in the world
• Communicate anytime, anywhere from the comfort of your home
• Advertising platforms for brands to find their right-set of consumers
• Easy to build relationships and connecting with like-minded people
• Easy access to desired information, products and services. 

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Kelsey Rzepecki

Multimedia blog, feature story: technology & youth.

The Influence of Technology and Social Media on Fostering of Relationships in Youngest Generation

By: Kelsey Rzepecki

Feature Writing 1- Professor Alice Tallmadge

As the clock strikes noon on another weekday, the teenagers of South Eugene High School in Eugene, Ore., emerge from the front doors in what resemble herds of sheep. Their eyes are glued to their iPhones and other media devices. Somehow they maneuver through neighborhoods and traffic. Numerous clusters form social circles outside the school property, eyes transfixed on their hand-held screens. Their bodies are present but physical interaction with each other is minimal.

The short lunch hour passes and the students slowly shuffle back into the doors of the school. A few boys on skateboards make their way along the sidewalk; barely stubbing the heels of the young girl walking in front of him, one of the boys looks up anxiously and takes his ear buds out, making a clean getaway.

All across the country, the newest technological devices are opening up means of communication that attracts the on the go lifestyle of societies youngest digital generation. Whether positive or negative, new media, from the internet to smart phone devices, are changing the ways the current generation relates to each other.

Some believe the avid usage of social media and texting gives teens a self-esteem boost and a deeper way to feel connected with their family members and friends. However, some parents are concerned that their children are at the mercy of the hypnotizing glare of the computer and cellphone screens, which are eating away at their social skills.

Developmental Psychologist Marilyn Price-Mitchell believes those fears are exaggerated.

“It’s going to be a different way of understanding the world but it can’t completely replace personalized relationships,” she says. She thinks technology will help members of this generation develop relationships in a different way that has never been done before.

A 2012 study by Common Sense Media of 1,030 teens found that 90 percent (nine out of 10), use various forms of social media. Texting dominates the everyday usage of media activity each day at 68 percent.

Parents who are frequent users of technology do not see the issue as problematic. André Chinn, Instructional Technology Coordinator at the University of Oregon and father of two, exposes his two kids, ages 6 and 8, to iOS devices such as iPhones and iPads daily.

“For the last hundred years technology has been facilitating relationships and communication. People may have been asking the same questions about the conventional telephone 50 years ago, he says. If something becomes an addiction, then it is a problem, but if not, “it’s just another tool.”

Technology has the ability to allow anyone to express and share their thoughts with the world without having to open their mouths.

Child advocate and journalist, Marjie Knudsen claims that social media such as Twitter and Facebook, provides a productive outlet of communication for teens and children as a brave, comfortable way for shy kids to express themselves.

According to a study by Common Sense Media, 52 percent of teens believe social networking positively helps their relationships with their friends; 37 percent believe it helps their relationships with their families, leaving only 6 percent of teens who think it hurts their relationships.

“Social media and technology allows for a more level of a playing field; as long as they can get access,” she says.

Others believe that, along with the productive aspects of new media and technology, comes some drawbacks. Some believe SAY the usage of texting and online communication compared to simple phone calls and face-to-face interaction leads to a “dumbing down” of conversations that are merely superficial and surface based.

Many students today, “don’t seem to have a clear sense of boundaries with adults and their peers. No subject seems to be off topic,” says Suzy Rock, 5th grade teacher at Howard Elementary School in Eugene, Ore.

Rock, who’s been teaching for 12 years, says she notices her students today seem to expect instant gratification and feedback, which doesn’t always happen in physical interactions with people.

The way in which people adapt to the introduction of new digital communication and technology will always have the potential to alter the level of human connectedness.

MIT Professor and Psychologist Sherry Turkle says digital communication is not productive for the degree of understanding and relationship-building you get when you are present with your friends sharing intimacies, difficult news, and overall for truly getting to know someone.

“There is a responsibility of intimacy that is necessary in the sense of genuinely connecting with someone,” she says.

Cindy Strickland, a businesswoman and mother of two teenagers, ages 18 and 16, is concerned that her son and daughter find it difficult to engage in simple interactions for an extended amount of time without the distractions from their technical devices.

“It’s the worst when I repeatedly remind them over and over of a simple task and they end up never doing it. It is frustrating because we rely on technology to stay connected with our kids when away, then face-to-face it effects them as well,” she says.

As an avid user of technology her children’s constant usage of technology.

Some people’s concerns regarding youth who are engaging in digital communication revolve around the lack of education of safety of disclosing personal information.

Many sources agree that there needs to be an effort to teach youth a healthy balance between using technology and being aware of its consequences. The importance of reputation in the lives of teenagers is a significant priority; now they are using social media as an up-to-date documentation and digital diary of their lives. Many teens don’t understand that their information can be seen by more people than they realize.

Sue Kanies, 7th grade teacher of 21 years, says she has witnessed students complaining about the lack of privacy and control they have over media. Some have boycotted certain social media sites completely.

“It’s assuring to see that they realize how these sites are effecting them and their relationships. I think they’re finally beginning to understand some of the repercussions that will eventually follow,” she says.

In a most recent study by Common Sense Media (SAME ONE AS ABOVE?) , 49 percent of teens 13 to 17 years old say their favorite way to communicate with a friend is in person, while 33 percent prefer texting.

Knudsen stresses the importance and awareness of creating healthy usage of technology, leaving it up to the individual in how they want to display their image of themselves in the scrutiny of the online world.

Chinn, the IT expert, says the lack of civility and discourse surrounding sites such as YouTube and chat rooms are his biggest concerns for his children. He says the discourse online in general is ugly and inappropriate, because anyone is able to hide behind their keyboard not having to reveal their true identity. This, he says, can be a result of a persons lack of security and self-esteem. Such individuals may use technology as an outlet to escape from the outside world.

Parents have a large effect and responsibility in teaching their children ways to be safe through digital communication, and also know when to intervene and determine if it progressively starts to alter their behavior.

Marilyn Price-Mitchell emphasizes the need in simply paying closer attention to the amount children use technology.

“Technology gives an escape from the world that they didn’t have before; if we’re not paying attention as adults, other online catastrophes are bound to happen,” she says. Technology is to be used wisely and with balance.

A recent study published by the Journal of Social and Personal Relationship found that the simple presence of cell phones hinders the development of feelings of closeness and trust, while reducing the amount of empathy people feel for others.

Kanies believes social media can become addictive, even though her students may complain about it, “I can tell some students feed off of it and feel the need to be connected just so they can stay in the loop; even if they are not active online, they want to have a presence,” she says.

5 thoughts on “ Feature Story: Technology & Youth ”

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• Open access
• Published: 18 May 2024

Emotions unveiled: detecting COVID-19 fake news on social media

• Bahareh Farhoudinia   ORCID: orcid.org/0000-0002-2294-8885 1 ,
• Selcen Ozturkcan   ORCID: orcid.org/0000-0003-2248-0802 1 , 2 &
• Nihat Kasap   ORCID: orcid.org/0000-0001-5435-6633 1  

Humanities and Social Sciences Communications volume  11 , Article number:  640 ( 2024 ) Cite this article

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The COVID-19 pandemic has highlighted the pernicious effects of fake news, underscoring the critical need for researchers and practitioners to detect and mitigate its spread. In this paper, we examined the importance of detecting fake news and incorporated sentiment and emotional features to detect this type of news. Specifically, we compared the sentiments and emotions associated with fake and real news using a COVID-19 Twitter dataset with labeled categories. By utilizing different sentiment and emotion lexicons, we extracted sentiments categorized as positive, negative, and neutral and eight basic emotions, anticipation, anger, joy, sadness, surprise, fear, trust, and disgust. Our analysis revealed that fake news tends to elicit more negative emotions than real news. Therefore, we propose that negative emotions could serve as vital features in developing fake news detection models. To test this hypothesis, we compared the performance metrics of three machine learning models: random forest, support vector machine (SVM), and Naïve Bayes. We evaluated the models’ effectiveness with and without emotional features. Our results demonstrated that integrating emotional features into these models substantially improved the detection performance, resulting in a more robust and reliable ability to detect fake news on social media. In this paper, we propose the use of novel features and methods that enhance the field of fake news detection. Our findings underscore the crucial role of emotions in detecting fake news and provide valuable insights into how machine-learning models can be trained to recognize these features.

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Introduction.

Social media has changed human life in multiple ways. People from all around the world are connected via social media. Seeking information, entertainment, communicatory utility, convenience utility, expressing opinions, and sharing information are some of the gratifications of social media (Whiting and Williams, 2013 ). Social media is also beneficial for political parties or companies since they can better connect with their audience through social media (Kumar et al., 2016 ). Despite all the benefits that social media adds to our lives, there are also disadvantages to its use. The emergence of fake news is one of the most important and dangerous consequences of social media (Baccarella et al., 2018 , 2020 ). Zhou et al. ( 2019 ) suggested that fake news threatens public trust, democracy, justice, freedom of expression, and the economy. In the 2016 United States (US) presidential election, fake news engagement outperformed mainstream news engagement and significantly impacted the election results (Silverman, 2016 ). In addition to political issues, fake news can cause irrecoverable damage to companies. For instance, Pepsi stock fell by 4% in 2016 when a fake story about the company’s CEO spread on social media (Berthon and Pitt, 2018 ). During the COVID-19 pandemic, fake news caused serious problems, e.g., people in Europe burned 5G towers because of a rumor claiming that these towers damaged the immune system of humans (Mourad et al., 2020 ). The World Health Organization (WHO) asserted that misinformation and propaganda propagated more rapidly than the COVID-19 pandemic, leading to psychological panic, the circulation of misleading medical advice, and an economic crisis.

This study, which is a part of a completed PhD thesis (Farhoundinia, 2023 ), focuses on analyzing the emotions and sentiments elicited by fake news in the context of COVID-19. The purpose of this paper is to investigate how emotions can help detect fake news. This study aims to address the following research questions: 1. How do the sentiments associated with real news and fake news differ? 2. How do the emotions elicited by fake news differ from those elicited by real news? 3. What particular emotions are most prevalent in fake news? 4. How can these feelings be used to recognize fake news on social media?

This paper is arranged into six sections: Section “Related studies” reviews the related studies; Section “Methods” explains the proposed methodology; and Section “Results and analysis” presents the implemented models, analysis, and related results in detail. Section “Discussion and limitations” discusses the research limitations, and the conclusion of the study is presented in Section “Conclusion”.

Related studies

Research in the field of fake news began following the 2016 US election (Carlson, 2020 ; Wang et al., 2019 ). Fake news has been a popular topic in multiple disciplines, such as journalism, psychology, marketing, management, health care, political science, information science, and computer science (Farhoudinia et al., 2023 ). Therefore, fake news has not been defined in a single way; according to Berthon and Pitt ( 2018 ), misinformation is the term used to describe the unintentional spread of fake news. Disinformation is the term used to describe the intentional spread of fake news to mislead people or attack an idea, a person, or a company (Allcott and Gentzkow, 2017 ). Digital assets such as images and videos could be used to spread fake news (Rajamma et al., 2019 ). Advancements in computer graphics, computer vision, and machine learning have made it feasible to create fake images or movies by merging them together (Agarwal et al., 2020 ). Additionally, deep fake videos pose a risk to public figures, businesses, and individuals in the media. Detecting deep fakes is challenging, if not impossible, for humans.

The reasons for believing and sharing fake news have attracted the attention of several researchers (e.g., Al-Rawi et al., 2019 ; Apuke and Omar, 2020 ; Talwar, Dhir et al., 2019 ). Studies have shown that people have a tendency to favor news that reinforces their existing beliefs, a cognitive phenomenon known as confirmation bias. This inclination can lead individuals to embrace misinformation that aligns with their preconceived notions (Kim and Dennis, 2019 ; Meel and Vishwakarma, 2020 ). Although earlier research focused significantly on the factors that lead people to believe and spread fake news, it is equally important to understand the cognitive mechanisms involved in this process. These cognitive mechanisms, as proposed by Kahneman ( 2011 ), center on two distinct systems of thinking. In system-one cognition, conclusions are made without deep or conscious thoughts; however, in system-two cognition, there is a deeper analysis before decisions are made. Based on Moravec et al. ( 2020 ), social media users evaluate news using ‘system-one’ cognition; therefore, they believe and share fake news without deep thinking. It is essential to delve deeper into the structural aspects of social media platforms that enable the rapid spread of fake news. Social media platforms are structured to show that posts and news are aligned with users’ ideas and beliefs, which is known as the root cause of the echo chamber effect (Cinelli et al., 2021 ). The echo chamber effect has been introduced as an aspect that causes people to believe and share fake news on social media (e.g., Allcott and Gentzkow, 2017 ; Berthon and Pitt, 2018 ; Chua and Banerjee, 2018 ; Peterson, 2019 ).

In the context of our study, we emphasize the existing body of research that specifically addresses the detection of fake news (Al-Rawi et al., 2019 ; Faustini and Covões, 2020 ; Ozbay and Alatas, 2020 ; Raza and Ding, 2022 ). Numerous studies that are closely aligned with the themes of our present investigation have delved into methodological approaches for identifying fake news (Er and Yılmaz, 2023 ; Hamed et al., 2023 ; Iwendi et al., 2022 ). Fake news detection methods are classified into three categories: (i) content-based, (ii) social context, and (iii) propagation-based methods. (i) Content-based fake news detection models are based on the content and linguistic features of the news rather than user and propagation characteristics (Zhou and Zafarani, 2019 , p. 49). (ii) Fake news detection based on social context employs user demographics such as age, gender, education, and follower–followee relationships of the fake news publishers as features to recognize fake news (Jarrahi and Safari, 2023 ). (iii) Propagation-based approaches are based on the spread of news on social media. The input of the propagation-based fake news detection model is a cascade of news, not text or user profiles. Cascade size, cascade depth, cascade breadth, and node degree are common features of detection models (Giglietto et al., 2019 ; de Regt et al., 2020 ; Vosoughi et al., 2018 ).

Machine learning methods are widely used in the literature because they enable researchers to handle and process large datasets (Ongsulee, 2017 ). The use of machine learning in fake news research has been extremely beneficial, especially in the domains of content-based, social context-based, and propagation-based fake news identification. These methods leverage the advantages of a range of characteristics, including sentiment-related, propagation, temporal, visual, linguistic, and user/account aspects. Fake news detection frequently makes use of machine learning techniques such as logistic regressions, decision trees, random forests, naïve Bayes, and support vector machine (SVM). Studies on the identification of fake news also include deep learning models, such as convolutional neural networks (CNN) and long short-term memory (LSTM) networks, which can provide better accuracy in certain situations. Even with a small amount of training data, pretrained language models such as bidirectional encoder representations from transformers (BERT) show potential for identifying fake news (Kaliyar et al., 2021 ). Amer et al. ( 2022 ) investigated the usefulness of these models in benchmark studies covering different topics.

The role of emotions in identifying fake news within academic communities remains an area with considerable potential for additional research. Despite many theoretical and empirical studies, this topic remains inadequately investigated. Ainapure et al. ( 2023 ) analyzed the sentiments elicited by tweets in India during the COVID-19 pandemic with deep learning and lexicon-based techniques using the valence-aware dictionary and sentiment reasoner (Vader) and National Research Council (NRC) lexicons to understand the public’s concerns. Dey et al. ( 2018 ) applied several natural language processing (NLP) methods, such as sentiment analysis, to a dataset of tweets about the 2016 U.S. presidential election. They found that fake news had a strong tendency toward negative sentiment; however, their dataset was too limited (200 tweets) to provide a general understanding. Cui et al. ( 2019 ) found that sentiment analysis was the best-performing component in their fake news detection framework. Ajao et al. ( 2019 ) studied the hypothesis that a relationship exists between fake news and the sentiments elicited by such news. The authors tested hypotheses with different machine learning classifiers. The best results were obtained by sentiment-aware classifiers. Pennycook and Rand ( 2020 ) argued that reasoning and analytical thinking help uncover news credibility; therefore, individuals who engage in reasoning are less likely to believe fake news. Prior psychology research suggests that an increase in the use of reason implies a decrease in the use of emotions (Mercer, 2010 ).

In this study, we apply sentiment analysis to the more general topic of fake news detection. The focus of this study is on the tweets that were shared during the COVID-19 pandemic. Many scholars focused on the effects of media reports, providing comprehensive information and explanations about the virus. However, there is still a gap in the literature on the characteristics and spread of fake news during the COVID-19 pandemic. A comprehensive study can enhance preparedness efforts for any similar future crisis. The aim of this study is to answer the question of how emotions aid in fake news detection during the COVID-19 pandemic. Our hypothesis is that fake news carries negative emotions and is written with different emotions and sentiments than those of real news. We expect to extract more negative sentiments and emotions from fake news than from real news. Existing works on fake news detection have focused mainly on news content and social context. However, emotional information has been underutilized in previous studies (Ajao et al., 2019 ). We extract sentiments and eight basic emotions from every tweet in the COVID-19 Twitter dataset and use these features to classify fake and real news. The results indicate how emotions can be used in differentiating and detecting fake and real news.

With our methodology, we employed a multifaceted approach to analyze tweet text and discern sentiment and emotion. The steps involved were as follows: (a) Lexicons such as Vader, TextBlob, and SentiWordNet were used to identify sentiments embedded in the tweet content. (b) The NRC emotion lexicon was utilized to recognize the range of different emotions expressed in the tweets. (c) Machine learning models, including the random forest, naïve Bayes, and SVM classifiers, as well as a deep learning model, BERT, were integrated. These models were strategically applied to the data for fake news detection, both with and without considering emotions. This comprehensive approach allowed us to capture nuanced patterns and dependencies within the tweet data, contributing to a more effective and nuanced analysis of the fake news content on social media.

An open, science-based, publicly available dataset was utilized. The dataset comprises 10,700 English tweets with hashtags relevant to COVID-19, categorized with real and fake labels. Previously used by Vasist and Sebastian ( 2022 ) and Suter et al. ( 2022 ), the manually annotated dataset was compiled by Patwa et al. ( 2021 ) in September 2020 and includes tweets posted in August and September 2020. According to their classification, the dataset is balanced, with 5600 real news stories and 5100 fake news stories. The dataset used for the study was generated by sourcing fake news data from public fact-checking websites and social media outlets, with manual verification against the original documents. Web-based resources, including social media posts and fact-checking websites such as PolitiFact and Snopes, played a key role in collecting and adjudicating details on the veracity of claims related to COVID-19. For real news, tweets from official and verified sources were gathered, and each tweet was assessed by human reviewers based on its contribution of relevant information about COVID-19 (Patwa et al., 2021 ; Table 2 on p. 4 of Suter et al., 2022 , which is excerpted from Patwa et al. ( 2021 ), also provides an illustrative overview).

Preprocessing is an essential step in any data analysis, especially when dealing with textual data. Appropriate preprocessing steps can significantly enhance the performance of the models. The following preprocessing steps were applied to the dataset: removing any characters other than alphabets, change the letters to lower-case, deleting stop words such as “a,” “the,” “is,” and “are,” which carry very little helpful information, and performing lemmatization. The text data were transformed into quantitative data by the scikit-learn ordinal encoder class.

The stages involved in this research are depicted in a high-level schematic that is shown in Fig. 1 . First, the sentiments and emotions elicited by the tweets were extracted, and then, after studying the differences between fake and real news in terms of sentiments and emotions, these characteristics were utilized to construct fake news detection models.

The figure depicts the stages involved in this research in a high-level schematic.

Sentiment analysis

Sentiment analysis is the process of deriving the sentiment of a piece of text from its content (Vinodhini and Chandrasekaran, 2012 ). Sentiment analysis, as a subfield of natural language processing, is widely used in analyzing the reviews of a product or service and social media posts related to different topics, events, products, or companies (Wankhade et al., 2022 ). One major application of sentiment analysis is in strategic marketing. Păvăloaia et al. ( 2019 ), in a comprehensive study on two companies, Coca-Cola and PepsiCo, confirmed that the activity of these two brands on social media has an emotional impact on existing or future customers and the emotional reactions of customers on social media can influence purchasing decisions. There are two methods for sentiment analysis: lexicon-based and machine-learning methods. Lexicon-based sentiment analysis uses a collection of known sentiments that can be divided into dictionary-based lexicons or corpus-based lexicons (Pawar et al., 2015 ). These lexicons help researchers derive the sentiments generated from a text document. Numerous dictionaries, such as Vader (Hutto and Gilbert, 2014 ), SentiWordNet (Esuli and Sebastiani, 2006 ), and TextBlob (Loria, 2018 ), can be used for scholarly research.

In this research, Vader, TextBlob, and SentiWordNet are the three lexicons used to extract the sentiments generated from tweets. The Vader lexicon is an open-source lexicon attuned specifically to social media (Hutto and Gilbert, 2014 ). TextBlob is a Python library that processes text specifically designed for natural language analysis (Loria, 2018 ), and SentiWordNet is an opinion lexicon adapted from the WordNet database (Esuli and Sebastiani, 2006 ). Figure 2 shows the steps for the sentiment analysis of tweets.

The figure illustrates the steps for the sentiment analysis of tweets.

Different methods and steps were used to choose the best lexicon. First, a random partition of the dataset was manually labeled as positive, negative, or neutral. The results of every lexicon were compared with the manually labeled sentiments, and the performance metrics for every lexicon are reported in Table 1 . Second, assuming that misclassifying negative and positive tweets as neutral is not as crucial as misclassifying negative tweets as classifying positive tweets, the neutral tweets were ignored, and a comparison was made on only positive and negative tweets. The three-class and two-class classification metrics are compared in Table 1 .

Third, this study’s primary goal was to identify the precise distinctions between fake and real tweets to improve the detection algorithm. We addressed how well fake news was detected with the three sentiment lexicons, as different results were obtained. This finding means that a fake news detection model was trained with the dataset using the outputs from three lexicons: Vader, TextBlob, and SentiWordNet. As previously indicated, the dataset includes labels for fake and real news, which allows for the application of supervised machine learning detection models and the evaluation of how well various models performed. The Random Forest algorithm is a supervised machine learning method that has achieved good performance in the classification of text data. The dataset contains many tweets and numerical data reporting the numbers of hospitalized, deceased, and recovered individuals who do not carry any sentiment. During this phase, tweets containing numerical data were excluded; this portion of the tweets constituted 20% of the total. Table 2 provides information on the classification power using the three lexicons with nonnumerical data. The models were more accurate when using sentiments drawn from Vader. This finding means the Vader lexicon may include better classifications of fake and real news. Vader was selected as the superior sentiment lexicon after evaluating all three processes. The steps for choosing the best lexicon are presented in Fig. 3 (also see Appendix A in Supplementary Information for further details on the procedure). Based on the results achieved when using Vader, the tweets that are labeled as fake include more negative sentiments than those of real tweets. Conversely, real tweets include more positive sentiments.

The figure exhibits the steps for choosing the best lexicon.

Emotion extraction

Emotions elicited in tweets were extracted using the NRC emotion lexicon. This lexicon measures emotional effects from a body of text, contains ~27,000 words, and is based on the National Research Council Canada’s affect lexicon and the natural language toolkit (NLTK) library’s WordNet synonym sets (Mohammad and Turney, 2013 ). The lexicon includes eight scores for eight emotions based on Plutchick’s model of emotion (Plutchik, 1980 ): joy, trust, fear, surprise, sadness, anticipation, anger, and disgust. These emotions can be classified into four opposing pairs: joy–sadness, anger–fear, trust–disgust, and anticipation–surprise. The NRC lexicon assigns each text the emotion with the highest score. Emotion scores from the NRC lexicon for every tweet in the dataset were extracted and used as features for the fake news detection model. The features of the model include the text of the tweet, sentiment, and eight emotions. The model was trained with 80% of the data and tested with 20%. Fake news had a greater prevalence of negative emotions, such as fear, disgust, and anger, than did real news, and real news had a greater prevalence of positive emotions, such as anticipation, joy, and surprise, than did fake news.

Fake news detection

In the present study, the dataset was divided into a training set (80%) and a test set (20%). The dataset was analyzed using three machine learning models: random forest, SVM, and naïve Bayes. Appendices A and B provide information on how the results were obtained and how they correlate with the research corpus.

Random forest : An ensemble learning approach that fits several decision trees to random data subsets. This classifier is popular for text classification, high-dimensional data, and feature importance since it overfits less than decision trees. The Random Forest classifier in scikit-learn was used in this study (Breiman, 2001 ).

Naïve Bayes : This model uses Bayes’ theorem to solve classification problems, such as sorting documents into groups and blocking spam. This approach works well with text data and is easy to use, strong, and good for problems with more than one label. The Naïve Bayes classifier from scikit-learn was used in this study (Zhang, 2004 ).

Support vector machines (SVMs) : Supervised learning methods that are used to find outliers, classify data, and perform regression. These methods work well with data involving many dimensions. SVMs find the best hyperplanes for dividing classes. In this study, the SVM model from scikit-learn was used (Cortes and Vapnik, 1995 ).

Deep learning models can learn how to automatically describe data in a hierarchical way, making them useful for tasks such as identifying fake news (Salakhutdinov et al., 2012 ). A language model named bidirectional encoder representations from transformers (BERT) was used in this study to help discover fake news more easily.

BERT : A cutting-edge NLP model that uses deep neural networks and bidirectional learning and can distinguish patterns on both sides of a word in a sentence, which helps it understand the context and meaning of text. BERT has been pretrained with large datasets and can be fine-tuned for specific applications to capture unique data patterns and contexts (Devlin et al., 2018 ).

In summary, we applied machine learning models (random forest, naïve Bayes, and SVM) and a deep learning model (BERT) to analyze text data for fake news detection. The impact of emotion features on detecting fake news was compared between models that include these features and models that do not include these features. We found that adding emotion scores as features to machine learning and deep learning models for fake news detection can improve the model’s accuracy. A more detailed analysis of the results is given in the section “Results and analysis”.

Results and analysis

In the sentiment analysis using tweets from the dataset, positive and negative sentiment tweets were categorized into two classes: fake and real. Figure 4 shows a visual representation of the differences, while the percentages of the included categories are presented in Table 3 . In fake news, the number of negative sentiments is greater than the number of positive sentiments (39.31% vs. 31.15%), confirming our initial hypothesis that fake news disseminators use extreme negative emotions to attract readers’ attention.

The figure displays a visual representation of the differences of sentiments in each class.

Fake news disseminators aim to attack or satirize an idea, a person, or a brand using negative words and emotions. Baumeister et al. ( 2001 ) suggested that negative events are stronger than positive events and that negative events have a more significant impact on individuals than positive events. Accordingly, individuals sharing fake news tend to express more negativity for increased impressiveness. The specific topics of the COVID-19 pandemic, such as the source of the virus, the cure for the illness, the strategy the government is using against the spread of the virus, and the spread of vaccines, are controversial topics. These topics, known for their resilience against strong opposition, have become targets of fake news featuring negative sentiments (Frenkel et al., 2020 ; Pennycook et al., 2020 ). In real news, the pattern is reversed, and positive sentiments are much more frequent than negative sentiments (46.45% vs. 35.20%). Considering that real news is spread among reliable news channels, we can conclude that reliable news channels express news with positive sentiments so as not to hurt their audience psychologically and mentally.

The eight scores for the eight emotions of anger, anticipation, disgust, fear, joy, sadness, surprise, and trust were extracted from the NRC emotion lexicon for every tweet. Each text was assigned the emotion with the highest score. Table 4 and Fig. 5 include more detailed information about the emotion distribution.

The figure depicts more detailed information about the emotion distribution.

The NRC lexicon provides scores for each emotion. Therefore, the intensities of emotions can also be compared. Table 5 shows the average score of each emotion for the two classes, fake and real news.

A two-sample t -test was performed using the pingouin (PyPI) statistical package in Python (Vallat, 2018 ) to determine whether the difference between the two groups was significant (Tables 6 and 7 ).

As shown in Table 6 , the P values indicate that the differences in fear, anger, trust, surprise, disgust, and anticipation were significant; however, for sadness and joy, the difference between the two groups of fake and real news was not significant. Considering the statistics provided in Tables 4 , 5 , and Fig. 5 , the following conclusions can be drawn:

Anger, disgust, and fear are more commonly elicited in fake news than in real news.

Anticipation and surprise are more commonly elicited in real news than in fake news.

Fear is the most commonly elicited emotion elicited in both fake and real news.

Trust is the second most commonly elicited emotion in fake and real news.

The most significant differences were observed for trust, fear, and anticipation (5.92%, 5.33%, and 3.05%, respectively). The differences between fake and real news in terms of joy and sadness were not significant.

In terms of intensity, based on Table 5 ,

Fear is the mainly elicited emotion in both fake and real news; however, fake news has a higher fear intensity score than does real news.

Trust is the second most commonly elicited emotion in two categories—real and fake—but is more powerful in real news.

Positive emotions, such as anticipation, surprise, and trust, are more strongly elicited in real news than in fake news.

Anger, disgust, and fear are among the stronger emotions elicited by fake news. Joy and sadness are elicited in both classes almost equally.

During the COVID-19 pandemic, fake news disseminators seized the opportunity to create fearful messages aligned with their objectives. The existence of fear in real news is also not surprising because of the extraordinary circumstances of the pandemic. The most crucial point of the analysis is the significant presence of negative emotions elicited by fake news. This observation confirms our hypothesis that fake news elicits extremely negative emotions. Positive emotions such as anticipation, joy, and surprise are elicited more often in real news than in fake news, which also aligns with our hypothesis. The largest differences in elicited emotions are as follows: trust, fear, and anticipation.

We used nine features for every tweet in the dataset: sentiment and eight scores for every emotion and sentiment in every tweet. These features were utilized for supervised machine learning fake news detection models. A schematic explanation of the models is given in Fig. 6 . The dataset was divided into training and test sets, with an 80%–20% split. The scikit-learn random forest, SVM, and Naïve Bayes machine learning models with default hyperparameters were implemented using emotion features to detect fake news in nonnumerical data. Then, we compared the prediction power of the models with that of models without these features. The performance metrics of the models, such as accuracy, precision, recall, and F1-score, are given in Table 7 .

The figure exhibits a schematic explanation of the model.

When joy and sadness were removed from the models, the accuracy decreased. Thus, the models performed better when all the features were included (see Table C.1. Feature correlation scores in Supplementary Information). The results confirmed that elicited emotions can help identify fake and real news. Adding emotion features to the detection models significantly increased the performance metrics. Figure 7 presents the importance of the emotion features used in the random forest model.

The figure illustrates the importance of the emotion features used in the Random Forest model.

In the random forest classifier, the predominant attributes were anticipation, trust, and fear. The difference in the emotion distribution between the two classes of fake and real news was also more considerable for anticipation, trust, and fear. It can be claimed that fear, trust, and anticipation emotions have good differentiating power between fake and real news.

BERT was the other model that was employed for the task of fake news detection using emotion features. The BERT model includes a number of preprocessing stages. The text input is segmented using the BERT tokenizer, with sequence truncation and padding ensuring that the length does not exceed 128 tokens, a reduction from the usual 512 tokens due to constraints on computing resources. The optimization process utilized the AdamW optimizer with a set learning rate of 0.00001. To ascertain the best number of training cycles, a 5-fold cross-validation method was applied, which established that three epochs were optimal. The training phase consisted of three unique epochs. The model was executed on Google Colab using Python, a popular programming language. The model was evaluated with the test set after training. Table 8 shows the performance of the BERT model with and without using emotions as features.

The results indicate that adding emotion features had a positive impact on the performance of the random forest, SVM, and BERT models; however, the naïve Bayes model achieved better performance without adding emotion features.

Discussion and limitations

This research makes a substantial impact on the domain of detecting fake news. The goal was to explore the range of sentiments and emotional responses linked to both real and fake news in pursuit of fulfilling the research aims and addressing the posed inquiries. By identifying the emotions provoked as key indicators of fake news, this study adds valuable insights to the existing corpus of related scholarly work.

Our research revealed that fake news triggers a higher incidence of negative emotions compared to real news. Sentiment analysis indicated that creators of fake news on social media platforms tend to invoke more negative sentiments than positive ones, whereas real news generally elicits more positive sentiments than negative ones. We extracted eight emotions—anger, anticipation, disgust, fear, joy, sadness, surprise, and trust—from each tweet analyzed. Negative and potent emotions such as fear, disgust, and anger were more frequently found elicited in fake news, in contrast to real news, which was more likely to arouse lighter and positive emotions such as anticipation, joy, and surprise. The difference in emotional response extended beyond the range of emotions to their intensity, with negative feelings like fear, anger, and disgust being more pronounced in fake news. We suggest that the inclusion of emotional analysis in the development of automated fake news detection algorithms could improve the effectiveness of the machine learning and deep learning models designed for fake news detection in this study.

Due to negativity bias (Baumeister et al., 2001 ), bad news, emotions, and feedback tend to have a more outsized influence than positive experiences. This suggests that humans are more likely to assign greater weight to negative events over positive ones (Lewicka et al., 1992 ). Our findings indicate that similar effects are included in social media user behavior, such as sharing and retweeting. Furthermore, the addition of emotional features to the fake news detection models was found to improve their performance, providing an opportunity to investigate their moderating effects on fake news dissemination in future research.

The majority of the current research on identifying fake news involves analyzing the social environment and news content (Amer et al., 2022 ; Jarrahi and Safari, 2023 ; Raza and Ding, 2022 ). Despite its possible importance, the investigation of emotional data has not received sufficient attention in the past (Ajao et al., 2019 ). Although sentiment in fake news has been studied in the literature, earlier studies mostly neglected a detailed examination of certain emotions. Dey et al. ( 2018 ) contributed to this field by revealing a general tendency toward negativity in fake news. Their results support our research and offer evidence for the persistent predominance of negative emotions elicited by fake news. Dey et al. ( 2018 ) also found that trustworthy tweets, on the other hand, tended to be neutral or positive in sentiment, highlighting the significance of sentiment polarity in identifying trustworthy information.

Expanding upon this sentiment-focused perspective, Cui et al. ( 2019 ) observed a significant disparity in the sentiment polarity of comments on fake news as opposed to real news. Their research emphasized the clear emotional undertones in user reactions to false material, highlighting the importance of elicited emotions in the context of fake news. Similarly, Dai et al. ( 2020 ) analyzed false health news and revealed a tendency for social media replies to real news to be marked by a more upbeat tone. These comparative findings highlight how elicited emotions play a complex role in influencing how people engage with real and fake news.

Our analysis revealed that the emotions conveyed in fake tweets during the COVID-19 pandemic are in line with the more general trends found in other studies on fake news. However, our research extends beyond that of current studies by offering detailed insights into the precise distribution and strength of emotions elicited by fake tweets. This detailed research closes a significant gap in the body of literature by adding a fresh perspective on our knowledge of emotional dynamics in the context of disseminating false information. Our research contributes significantly to the current discussion on fake news identification by highlighting these comparative aspects and illuminating both recurring themes and previously undiscovered aspects of emotional data in the age of misleading information.

The present analysis was performed with a COVID-19 Twitter dataset, which does not cover the whole period of the pandemic. A complementary study on a dataset that covers a wider time interval might yield more generalizable findings, while our study represents a new effort in the field. In this research, the elicited emotions of fake and real news were compared, and the emotion with the highest score was assigned to each tweet, while an alternative method could be to compare the emotion score intervals for fake and real news. The performance of detection models could be further improved by using pretrained emotion models and adding additional emotion features to the models. In a future study, our hypothesis that “fake news and real news are different in terms of elicited emotions, and fake news elicits more negative emotions” could be examined in an experimental field study. Additionally, the premises and suppositions underlying this study could be tested in emergency scenarios beyond the COVID-19 context to enhance the breadth of crisis readiness.

The field of fake news research is interdisciplinary, drawing on the expertise of scholars from various domains who can contribute significantly by formulating pertinent research questions. Psychologists and social scientists have the opportunity to delve into the motivations and objectives behind the creators of fake news. Scholars in management can offer strategic insights for organizations to deploy in countering the spread of fake news. Legislators are in a position to draft laws that effectively stem the flow of fake news across social media channels. In addition, the combined efforts of researchers from other academic backgrounds can make substantial additions to the existing literature on fake news.

The aim of this research was to propose novel attributes for current fake news identification techniques and to explore the emotional and sentiment distinctions between fake news and real news. This study was designed to tackle the subsequent research questions: 1. How do the sentiments associated with real news and fake news differ? 2. How do the emotions elicited by fake news differ from those elicited by real news? 3. What particular elicited emotions are most prevalent in fake news? 4. How could these elicited emotions be used to recognize fake news on social media? To answer these research questions, we thoroughly examined tweets related to COVID-19. We employed a comprehensive strategy, integrating lexicons such as Vader, TextBlob, and SentiWordNet together with machine learning models, including random forest, naïve Bayes, and SVM, as well as a deep learning model named BERT. We first performed sentiment analysis using the lexicons. Fake news elicited more negative sentiments, supporting the idea that disseminators use extreme negativity to attract attention. Real news elicited more positive sentiments, as expected from trustworthy news channels. For fake news, there was a greater prevalence of negative emotions, including fear, disgust, and anger, while for real news, there was a greater frequency of positive emotions, such as anticipation, joy, and surprise. The intensity of these emotions further differentiated fake and real news, with fear being the most dominant emotion in both categories. We applied machine learning models (random forest, naïve Bayes, SVM) and a deep learning model (BERT) to detect fake news using sentiment and emotion features. The models demonstrated improved accuracy when incorporating emotion features. Anticipation, trust, and fear emerged as significant differentiators between fake and real news, according to the random forest feature importance analysis.

The findings of this research could lead to reliable resources for communicators, managers, marketers, psychologists, sociologists, and crisis and social media researchers to further explain social media behavior and contribute to the existing fake news detection approaches. The main contribution of this study is the introduction of emotions as a role-playing feature in fake news detection and the explanation of how specific elicited emotions differ between fake and real news. The elicited emotions extracted from social media during a crisis such as the COVID-19 pandemic could not only be an important variable for detecting fake news but also provide a general overview of the dominant emotions among individuals and the mental health of society during such a crisis. Investigating and extracting further features of fake news has the potential to improve the identification of fake news and may allow for the implementation of preventive measures. Furthermore, the suggested methodology could be applied to detecting fake news in fields such as politics, sports, and advertising. We expect to observe a similar impact of emotions on other topics as well.

Data availability

The datasets analyzed during the current study are available in the Zenodo repository: https://doi.org/10.5281/zenodo.10951346 .

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Bahareh Farhoudinia (first author) conducted the research, retrieved the open access data collected by other researchers, conducted the analysis, and drafted the manuscript as part of her PhD thesis successfully completed at Sabancı University in the year 2023. Selcen Ozturkcan (second author and PhD co-advisor) provided extensive guidance throughout the research process, co-wrote sections of the manuscript, and offered critical feedback on the manuscript. Nihat Kasap (third author and PhD main advisor) oversaw the overall project and provided valuable feedback on the manuscript.

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Farhoudinia, B., Ozturkcan, S. & Kasap, N. Emotions unveiled: detecting COVID-19 fake news on social media. Humanit Soc Sci Commun 11 , 640 (2024). https://doi.org/10.1057/s41599-024-03083-5

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Do Facebook and Instagram influence your politics? 35,000 took a break to find out

Facebook and Instagram may not have quite the impact on people’s politics as some critics have feared. 

A study published Monday by researchers at Stanford University, Meta and other institutions found that a subset of 35,000 people who took breaks from Facebook and Instagram for six weeks before the 2020 presidential election didn’t significantly change their politics by the time the election came around. 

The researchers found that staying off the two social media apps, both part of parent company Meta, had nearly zero effect — at least in the short term — on how people viewed the candidates, whether they turned out to vote and how they perceived the legitimacy of the election. 

But the researchers also found that staying off Facebook, in particular, was a double-edged sword for understanding the world: Those who deactivated the app appear to be less likely to believe misinformation about the election but also less likely to be knowledgeable about general news. 

The research, published in the Proceedings of the National Academy of Sciences, is part of a broader study trying to understand how social media affects democracy. Under fire for years for upending how campaigns are run and how voters consume information, Meta formed a partnership with academics to grant them access to company-held data. University professors retain control over what they report. In the latest study, the authors said that Meta paid for the costs of the research but that it didn’t pay the researchers or their institutions.

Meta said in a statement Monday: “These findings are consistent with previous publications in this study in showing little impact on key political attitudes, beliefs or behaviors.” An earlier set of findings published in July concluded that Facebook had “significant ideological segregation” and that conservative sources dominated its news ecosystem. 

Academic researchers and social media users alike have been eager to understand, for example, whether so-called filter bubbles exist and if so what the practical effects are. Social media has been repeatedly blamed for “ ruining political discourse ,” spreading falsehoods and making polarization worse , and research into such questions is relatively young. 

A co-author of the latest study, Matthew Gentzkow, a Stanford economist, said one of the study’s findings was how little impact Facebook and Instagram seemed to have on polarization and divisiveness. 

“If we’re worried about those things, trying to control what people see on social media and whether they’re on social media may not be the most important lever,” he said in an interview. 

On issues such as immigration, mask requirements and policing, those who deactivated Facebook and Instagram remained polarized. 

But Gentzkow also said the study isn’t nearly the final word on the subject, because it was limited to the impact of Facebook and Instagram in a relatively narrow six-week time frame. 

“This study cannot say one way or the other — in a decadelong sense — whether social media is causing polarization or not,” he said. 

Researchers did find a small, unverified impact of Facebook use favoring Donald Trump, in which people who deactivated from Facebook were slightly more likely than others to vote for Joe Biden — the equivalent of 1.3% of Trump voters’ swinging to Biden. That could be because the Trump campaign was using Facebook more effectively or possibly because of other factors, the researchers wrote. Either way, they wrote, the difference “applies to the specific population that selected into our experiment” and “cannot be extrapolated to the broader population without strong assumptions.” 

The study bills itself as the “largest-scale evidence available to date on the effect of Facebook and Instagram access on political knowledge, attitudes, and behavior in a presidential election season.” It lists 32 co-authors from 14 institutions. 

Researchers didn’t look at the role of Facebook and Instagram after Election Day, when some supporters of Trump used them to promote allegations about election fraud and the company battled to take the allegations down . 

Meta worked with the researchers to find participants, placing invitations in people’s feeds in August and September 2020. And participation came with a financial incentive: $25 apiece for people who agreed to deactivate for one week and $150 for people to deactivate for six weeks. 

It’s not the first study to wonder what life is like for people not on social media. A study published in 2018, amid an online boycott called #DeleteFacebook, said that “the average Facebook user would require more than $1,000 to deactivate their account for one year.”

And in a study from 2019 , Gentzkow and other researchers found that deactivating Facebook for four weeks before the 2018 midterm elections had a variety of real-world implications, including increased self-reported happiness, reduced factual news knowledge and reduced political polarization. Gentzkow said more research would be needed to explore why that study showed reduced polarization but the most recent one did not. 

David Ingram covers tech for NBC News.

How should you approach your children's and teenagers' social media use?

Children's social media usage is again in the spotlight, with the SA government announcing a proposal to ban children under 14 from accessing sites such as TikTok, Instagram and Facebook and requiring those aged 14 and 15 to have parental consent to use the apps.

But with two-thirds of primary-school-aged children and most teenagers owning their own mobile-based screen devices , is banning or restricting your child's access to social media the answer — and is it a workable solution?

'The genie is out of the bottle'

Recent research from the University of Sydney reveals Australians over the age of 14 spend an average of six hours a week on social media, and according to the eSafety Commissioner's Digital Lives of Aussie Kids report, 12–13-year-olds use an average of 3.1 social media services.

Meanjin/Brisbane-based parenting and positive psychology expert Justin Coulson says "ultimately, the social media genie is out of the bottle, and we're not getting the three wishes we hoped for".

"The great challenge that we have as parents is: how do we stuff the toothpaste back into the tube? And I just don't believe that it can be done," Dr Coulson says.

"I don't think we can make any strong arguments that [social media] has been a net positive for not just our children and youth, but for our society and for our community."

As a parent of six, including two daughters currently in their teens, Dr Coulson says ideally, he would like them "to be on social media less and use their screens less".

But the reality, he adds, is "they'll be isolated from their friends, they'll be isolated from activities that are being planned, and as much as it would be nice for their friends to send them a quick text … it's probably not going to happen because they all communicate on their various social platforms".

Setting boundaries requires trust

Some parents have opted to impose their own age restrictions on their children's social media use, including Jemma Guthrie and her partner Scott Carsdale, who recently shared how they kept their daughter off social media until she turned 15.

Ms Guthrie says restricting her daughter's social media access "wasn't a hard decision" and "came naturally based on a shared belief [with her partner] that offline life is better for children".

"I think it's hard to do if you haven't already established a culture of limit-setting in your own household," she says.

Dr Coulson says in order to establish boundaries and set limits "there's got to be a foundation of trust".

"My definition of trust is really simple; it's believing the other person is going to act in your best interests.

"So if you say 'no social media until 16 or 18' and [your children] don't believe that that's in their best interest, they don't believe you're going to act in their best interests, then no matter what you do, you're going to be diminishing yourself in their eyes and reducing your influence."

He says one of the primary roles of parenting is to socialise children and teach them values and morality, both online and off.

"The rules around social media are exactly the same as the rules around living a good life: There are rules around respect, consent, kindness, and support.

"Because if we're raising good kids, they'll be good kids, whether they're online or offline."

University of Sydney Media and Communications lecturer Catherine Page Jeffery specialises in research on parenting in the digital age, and says there is no simple fix.

"The problem is if you say 'no, you're not having it at all', and then they just go behind your back … they're not going to come to you if they have any problems or experience any difficulties in those spaces."

Is there a 'right age' to join social media?

Dr Page Jeffery says while social media may negatively affect some young people's wellbeing, that's not always the case.

"There is no magic age at which young people suddenly are bestowed with all of the skills and competencies to effectively navigate social media."

She explains children develop at different rates and have different levels of maturity, and some younger people "are much more sensible and risk-averse than others".

"Bearing that in mind, parents should really make their own judgement about when their child should or might be allowed to go on to social media.

"Obviously that depends on the age of the child, you probably wouldn't let a six- or seven-year-old [on social media apps] unseen and unsupervised, but certainly with older children, I think giving them some agency but providing support is not a bad approach."

The difference between risk and harm

Dr Page Jeffery acknowledges there is a steady stream of media reporting about research into the potentially adverse effects of social media on children and teenagers — including links between social media use and poor mental health and low self-esteem — but says those studies "often don't show causation".

"Parents hear about studies … and then their kids want to get on [social media] and their kids say, 'Look, I use it, and it's good for me, and this is what I get out of it', so parents are really conflicted."

"It's really hard, and you know what? I think letting your kids go and explore online spaces is not as bad as it sounds, as long as you can put some parameters and guidelines in place."

She accepts there are very real risks and says "of course, there needs to be certain mechanisms to address those risks", but warns it is important not to conflate risk with harm.

"Exposure to some risk and navigating risk is a really important part of young people's development.

"It teaches them the sort of skills they need to safely manage online spaces, and also helps them develop resilience."

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Age verification for social media would impact all of us. We asked parents and kids if they actually want it

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Catherine Page Jeffery has received funding from the Office of the eSafety Commissioner under the Online Safety Grants Program. She is affiliated with Children and Media Australia.

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This month the Australian government announced a A$6.5 million commitment to trial an age-verification program that will restrict children’s exposure to inappropriate online content, including pornography and potentially social media. The announcement came out of a National Cabinet meeting geared towards addressing gender-based violence in Australia.

Much has been said about age-checking technologies in the weeks since. Experts point out implementing these tools effectively (so they aren’t easily by-passed) will be complicated – and any such system could come with data security risk. Internet freedom groups have criticised the decision on account of its potential to erode privacy.

There is, however, an important dimension missing from these discussions: the voice of young people and parents. In our research into social media use and online harms affecting Australian teenagers, we asked young people and their parents what they themselves thought about age verification. We found mixed reactions from both groups.

Our findings suggest age verification is generally supported, but participants think it likely would not work. Instead, they said more safety education, face-to-face dialogue, and accountability from social media companies would be better approaches to keeping young people safe online.

Young Australians and social media

Young Australians use social media for a variety of reasons, from keeping in touch with friends and family, to seeking information and entertainment.

Our latest research found almost a quarter of young people 12 to 17 use WhatsApp daily. One in two are daily Snapchat users. Instagram and YouTube are the most frequently used platforms, used daily by 64% and 56% of young people respectively.

These patterns are especially significant for culturally and linguistically diverse Australians, who are more likely to use social media to socialise, maintain familial and cultural ties and learn about the world.

That said, social media and the internet more broadly do present risks to young people . These risks include online bullying, grooming and unsolicited contact, privacy breaches, misinformation and content that is pornographic, racist, sexist, homophobic and/or violent.

Studies have found associations between social media use and poor mental health and self-esteem , although direct causation is difficult to establish. It’s also important to note risk doesn’t equate with harm, and young people themselves commonly demonstrate skills, judgement and agency in negotiating online risks.

In an environment of heightened concern, decisions are now being made that will have significant impacts on both young people and their parents. These decisions are being fuelled by media brands, celebrities and ex-politicians seeking to influence discourse .

Elsewhere in the world, the UK’s Online Safety Bill is attempting to restrict young people’s access to online pornography, through either government-issued documents or biometrics . The UK regulator Ofcom is set to publish guidance on age-assurance compliance in early 2025 . France has also been testing a system to verify age based on a user intermediary , after it enacted a law in 2023 to restrict social media use for people under 15.

The details of the trial in Australia haven’t yet been released, but it could use one or a combination of approaches.

The missing perspective

Our research, which focused on Australian teenagers aged 12–17 and their parents, drew from focus groups and a national survey in 2022–23. Overall, the survey showed broad support for age verification. Specifically, 72% of young people and 86% of parents believed more effective age limits would improve online safety for young people.

But we also heard about several drawbacks. For instance, young people saw age verification as something that would benefit adults. One participant said:

I guess it benefits parents who want to be in the right mindset that their kids are safe on social media.

Another young person said:

I feel like in the case of lot of controlling parents it would be bad for the kid because then if the parents are controlling and they don’t have any social media to talk to people, I feel like that could negatively impact the kid. Maybe they’d get lonely, or they wouldn’t be able to use it as an outlet.

Some young people noted they could find ways around age-verification tools:

It would be simple just to get a VPN and change my country if it was going to create this obstacle.

They also pointed out such tools don’t account for evolving maturity levels and differing capabilities among young individuals.

Parents shared concerns about the burden of providing proof of their age and managing consent:

I mean depending on what kind of site it is would you be comfortable providing your passport information or your driver’s licence?

Both groups were worried about the risk of data breaches and leaks of sensitive information. As one parent told us:

Well, it certainly makes you think about it a lot more. What are they using that data for? Is it really just for age verification, or is it for something more nefarious?

Another young person also had privacy concerns:

But if I would say that I was OK with it, I think I’d be lying. Because, I’m a really private person, privacy really matters. And yeah, I do think to be safe, I think we really should be having our own privacy as well.

So what should be done?

Governments, parents, educators and platforms all have an important role to play in ensuring young people’s safety online.

Beyond age verification, there’s a growing consensus social media companies should be doing more to ensure users’ safety. Until that happens, the best approach is for parents and children to talk to each other to determine the appropriate age for a child to be on social media. By working together, families can develop guidelines and expectations for appropriate use.

Schools can also help by developing young people’s digital literacy and online safety skills.

Ultimately, if we want young people to thrive in online environments, we need to involve them in the decisions that will directly affect them.

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Meta Faces Fresh Probe Over ‘Addictive’ Effect on Kids

The European Union has opened an investigation into Facebook and Instagram for the platforms’ potentially addictive effects on children, echoing two similar probes opened into TikTok earlier this year .

Meta-owned platforms will be investigated for their addictive and “rabbit hole” effects, and whether young users were being fed too much content about depression or unrealistic body images. Investigators will also probe whether underage children below 13 years old are being effectively blocked from using the services.

“We are not convinced that Meta has done enough to comply with the DSA [Digital Services Act] obligations—to mitigate the risks of negative effects to the physical and mental health of young Europeans on its platforms Facebook and Instagram,” Thierry Breton, the EU’s internal markets commissioner who is leading the investigations, said on X.

“We want young people to have safe, age-appropriate experiences online,” said Meta spokesperson Kirstin MacLeod, adding the company has developed more than 50 tools and policies designed to protect young people. “This is a challenge the whole industry is facing, and we look forward to sharing details of our work with the European Commission.”

The investigations into Meta and TikTok under the bloc’s new Digital Services Act rules were separate, a commission spokesperson said, adding that similarities between the cases simply reflected resemblances in how the platforms work. “There are some competitive effects in the markets where some platforms copy other platforms’ features,” they said.

The effects of social media on children has sparked intense debate in recent months, following the publication of the book The Anxious Generation by Jonathan Haidt. The NYU social psychologist argues that the prevalence of social media use among young people is rewiring children’s brains and making them more anxious. In October, a coalition of US states sued Meta , alleging the company’s products are harmful to children’s mental health.

The Digital Services Act is an expansive rulebook that aims to protect Europeans’ human rights online and took effect for the largest platforms in August last year. So far, the EU has investigations open into six platforms for different reasons: AliExpress, Facebook, Instagram, TikTok, TikTok Lite, and X. Under the Digital Services Act, platforms can be fined up to 6 percent of their global revenue.

After the EU launched an investigation into a points-for-views reward system on TikTok Lite—a version of the app which uses less data—the company said it would suspend the incentive following concerns about its impact on children.

“Our children are not guinea pigs for social media,” Breton said at the time.

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By Emily Mullin

By Steven Levy

By Andy Greenberg

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