After recently celebrating its 15th anniversary, Facebook remains the top social networking site in the world (Hootsuite & We Are Social, 2020). With just over 2.6 billion users globally, Facebook users represent approximately one-third of the world’s population. US users comprise approximately 10% of that total, or 240 million, which is nearly 70% of our population (Gramlich, 2018). Now that new user growth has slowed, that number isn’t expected to change much over the next several years. Most of the increased use in the social space will occur on other networks, including networks that Facebook owns – Instagram, WhatsApp, and Messenger. Globally, it’s estimated these four networks total more than six billion users, not accounting for duplication across users (Hootsuite & We Are Social, 2020).
As the number of social networking sites continues to grow, so does the amount of time we spend on them daily. In 2012, eMarketer estimated that most US adults spent an average of four minutes a day on social media. Five years later, that amount of time increased to 50 minutes per day. At the end of 2019, US adults spent more than 75 minutes per day on social media (Williamson, 2020). That increase can likely be correlated to the psychology of gambling that most social platforms employ when coding their sites (Price, 2018). There is a reason that little notification button has a red bubble with numbers on it – to hook people’s attention and keep them on a network for as long as possible while sharing our most intimate thoughts, feelings, life events, and imagery with friends and near-strangers alike.
This has allowed networks to amass large amounts of personal data on users’ age, gender, income, employment, interests, travel habits, behaviors, likes, dislikes, food preferences, music preferences, workout routines, and anything else you can imagine. In fact, a former product manager at Facebook, Antonio García Martínez, wrote in his memoir Chaos Monkeys, the company has “the biggest accumulation of personal data since DNA” (Price, 2018).
Emotional Contagion Leads to Greater Profit
As of 10 years ago, digital media companies received just 15% of all advertising spend in the U.S. That share has more than tripled in the past decade, totaling nearly half of all advertising spend (Johnson, 2019). Through various online experiments and extensive research on customer behavior, digital and social networks have discovered the longer someone spends on their platform, the better opportunity to hijack someone’s attention, leading to greater profit. The methodology was borrowed directly from slot machines, which are incredibly addictive (Price, 2018).
As time spent on social media has increased over the past 10 years, various studies have signaled a strong link between internet usage and increased suicide rates (Shah, 2010; as cited in Sumner et al., 2020). Regardless, social networks have continued to maintain a vested interest in keeping users on their respective sites. Sites that are better at “gaming” the brain can keep users engaged for longer and stand to make a substantial profit. In 2020, Facebook and Google are estimated to receive 56% of all digital advertising spend, or around $88 billion in revenue (Peterson, 2019). Although there is a wide array of research on the impacts social media has on the mental well-being, most of the studies are cross-sectional and do not examine changes over time.
Social networks themselves periodically run user experiments to determine whether people’s emotional states can spread via their social connections, as well as ascertain what type of emotional states receive the greatest amount of interaction. In one study, Facebook deliberately adjusted the content of news feeds for 689,003 Facebook users to see whether their mood would be affected. The 2014 study showed definitive evidence that emotional contagion can occur via news feeds, without direct interaction between individuals, as “people who had positive content reduced in their News Feed, a larger percentage of words in people’s status updates were negative and a smaller percentage were positive. When negativity was reduced, the opposite pattern occurred” (Kramer et al., 2014). A separate study of the Chinese network, Weibo, demonstrated that posts eliciting an anger response had a stronger correlation to emotional influence than those attempting to spark joy (Fan et al., 2014).
Historically, unchecked propaganda has garnered greater attention over well-written, researched news stories. As such, Facebook’s algorithm has been purposefully coded and continually tweaked, to spread misinformation more efficiently to more people than any media outlet in history to continually increase ad revenue and shareholder profitability (Rose-Stockwell, 2017). However, unlike other mass media outlets, there is little government oversight to restrict social media networks from accessing private information. There has been little government oversight to discourage networks from using discriminatory practices when it comes to how or when ads are served to their users either – it’s been left up to private, civil rights organizations to police each outlet’s business practices (ACLU et al., 2019).
Once the network for broadcasting news alerts and updates quickly, Twitter has become the primary platform for cyberbullying, harassment, and hate speech (Warzel, 2016). It is frequently used by law enforcement to track protestors and quell free speech (Guynn, 2016). Since it is conversational in nature, it is also the platform people turn to for gossip and unsubstantiated claims, causing frequent meltdowns over the smallest of slights which only further isolates us from ourselves. Consequently, the number of users is dwindling, suggesting people have a limit to the amount of negative content they will allow themselves to be exposed to daily.
Can People Use Social Media More Positively?
People join social networks in order to feel connected to others – one positive outcome is that social media encourages more face-to-face connections (Sabatini, 2017). Additional research has shown that social media can benefit users by aiding in the development of social skills, providing access to a greater wealth of resources, and helping people create a sense of connection and belonging (2011, 2016, 2018; as cited in Appel et al., 2020). This may provide some explanation as to why sharing of positive messages to support certain mental health-related topics are more often shared than others, especially when a user’s socioeconomic status prohibits the user from gaining access to face-to-face resources to address their illness (Sumner et al., 2019).
A smaller subsection of research has correlated positive outcomes to social media use for mental well-being. The user’s level of emotional connection to social media is seen as a primary factor in determining positive or negative associations with social media. When considering the pathology of gambling disorders, emotional dysregulation of positive emotions may play a central role in the disorder (Rogier & Velotti, 2018). However, the research is currently limited, and further study is needed to distinguish the relationship between social media and positive mental health (Bekalu et al., 2019).
A separate study looking at the relation of positive and negative social media experiences to feelings of social isolation concluded that positive experiences were not associated with lower social isolation. However, negative experiences were associated with higher feelings of social isolation (Primack et al., 2019). These findings are consistent with the concept of negativity bias, which suggests that people weigh negative experiences more heavily when compared to positive ones.
The Future of Social Media
Social media has become a primary channel for consumers to receive vast amounts of information, from their friends and marketers alike. As such, it is a vital communication outlet for individuals, businesses, and institutions. The social landscape is in constant flux as technology advances rapidly and users find new ways to use the tools available (Appel et al., 2020). With the creation of mobile apps also came the integration of social networks into the fabric of individuals’ everyday life. Users now have the ability to access social networks for travel, dining, news, work, sports, music, checking in on family and friends, private communications, and more.
An individual can not only check in with their network for recommendations on restaurants, but they also have the ability to amplify their complaints if their experience wasn’t what they had expected. This suggests an “omni-social” type presence in our daily lives giving marketers the ability to increase the number of advertising messages to influence a consumer’s decision-making process from beginning to end (Appel et al., 2020). This has created opportunities for marketers to capitalize on the influence of celebrities, and other well-known public figures, as part of their strategies.
It has also increased concerns over data privacy and access to potentially harmful content, as networks continually harvest users’ data then sell it to the highest bidder, in an effort to more “personalized” advertising focused on the individual’s interests and behaviors (Price, 2018). However, social networks have been met with consumer backlash as the amount of negative subject matter has increased in recent years. Users also see brands as being complicit in curbing the amount of misinformation spread across social media. This has led to an increase in the number of people deactivating at least one of their social media accounts (2018; as cited in Appel et al., 2020). Insiders from Silicon Valley have publicly shared their concerns on the harmful effects of social media use, as well. Sean Parker, the founding president of Facebook, believes social media “literally changes your relationship with society, [and] with each other” (Price, 2018).
Users often overestimate the utility they will receive from social media use (Sabatini, 2017). If the user or social marketer is aware of their associated outcomes and intended use, more positive results can prevail. While networks have previously taken a hands-off approach towards restricting or removing content, advertisers are now demanding a more family-friendly environment in which to promote their brands. Social media networks are designed based on the psychology of gambling, and the attention economy, not on the quality of user content. This has led to the current state of what news media is calling “social media’s big tobacco moment.”
It is time for governments to intercede on behalf of users’ mental health and wellness. Historically, health departments have intervened to inform consumers of the potential hazards of engaging with potentially addictive substances and behavior, as well as provide resources and information about treatment. Government regulation also needs to address major concerns that are currently eroding public trust and well-being: protecting user information and privacy, addressing overall community standards, and allowing users to employ better content filters. Further longitudinal research is needed to determine whether the emotional response and biological patterns are similar to addiction, as well as help determine options for intervention.
ACLU, NFHA, CWA, ECBA, O&G, & Facebook (2019, March 19). Summary of settlements between civil rights advocates and Facebook. ACLU. https://www.aclu.org/other/summary-settlements-between-civil-rights-advocates-and-facebook
Appel G, Grewal L, Hadi R, Stephen AT. The future of social media in marketing. J Acad Mark Sci. 2020;48(1):79-95. https://doi.org/10.1007/s11747-019-00695-1
Bekalu, M. A., McCloud, R. F., & Viswanath, K. (2019). Association of Social Media Use with Social Well-Being, Positive Mental Health, and Self-Rated Health: Disentangling Routine Use From Emotional Connection to Use. Health Education & Behavior: The Official Publication of the Society for Public Health Education, 46(2_suppl), 69–80. https://doi.org/10.1177/1090198119863768
Fan R, Zhao J, Chen Y, Xu K (2014). Anger is more influential than joy: sentiment correlation in Weibo. PLoS ONE 9(10): e110184. https://doi.org/10.1371/journal.pone.0110184
Gramlich, J. (2019, May 16). 10 Facts about Americans and Facebook. Pew Research Center.https://www.pewresearch.org/fact-tank/2019/05/16/facts-about-americans-and-facebook/
Guynn, J. (2016, October 11). ACLU: Police used Twitter, Facebook to track protests. USA Today. https://www.usatoday.com/story/tech/news/2016/10/11/aclu-police-used-twitter-facebook-data-track-protesters-baltimore-ferguson/91897034/
Hootsuite and We Are Social (2020). Global social media overview. DataReportal. https://datareportal.com/social-media-users
Johnson, B. (2019, December 30). Internet media’s share of U.S. ad spending has more than tripled over the past decade. AdAge. https://adage.com/article/year-end-lists-2019/internet-medias-share-us-ad-spending-has-more-tripled-over-past-decade/2221701
Kramer, A. D. I., Guillory, J. E., & Hancock, J. T. (2014). Experimental evidence of massive-scale emotional contagion through social networks. PNAS June 17, 2014, 111 (24) 8788-8790; first published June 2, 2014. https://doi.org/10.1073/pnas.1320040111
Peterson, T. (2019, November 6). The ad-tech trends rounding out 2019: programmatic growth, measurement standards, privacy implications. Marketing Land. https://marketingland.com/the-adtech-trends-rounding-out-2019-programmatic-growth-measurement-standards-privacy-implications-269722
Price, C. (2018, October 29). Trapped – the secret ways social media is built to be addictive (and what you can do to fight back). Science Focus. https://www.sciencefocus.com/future-technology/trapped-the-secret-ways-social-media-is-built-to-be-addictive-and-what-you-can-do-to-fight-back/
Primack, B. A., Karim, S. A., Shensa, A., Bowman, N., Knight, J., & Sidani, J. E. (2019). Positive and Negative Experiences on Social Media and Perceived Social Isolation. American Journal of Health Promotion: AJHP, 33(6), 859–868. https://doi.org/10.1177/0890117118824196
Rogier, G., & Velotti, P. (2018). Conceptualizing gambling disorder with the process model of emotion regulation. Journal of Behavioral Addictions, 7(2), 239–251. https://doi.org/10.1556/2006.7.2018.52
Rose-Stockwell, T. (2017, July 28). This is how your fear and outrage are being sold for profit. Quartz.https://qz.com/1039910/how-facebooks-news-feed-algorithm-sells-our-fear-and-outrage-for-profit/
Sabatini, F., & Sarracino, F. (2017). Online Networks and Subjective Well-Being. Kyklos, 70(3), 456–480. https://doi.org/10.1111/kykl.12145
Sumner, S. A., Bowen, D. A., & Bartholow, B. (2020). Factors associated with increased dissemination of positive mental health messaging on social media. Crisis: The Journal of Crisis Intervention and Suicide Prevention, 41(2), 141–145. https://doi.org/10.1027/0227-5910/a000598 (Supplemental)
Warzel, C. (2016, August 16). “A Honeypot for Assholes”: Inside Twitter’s 10-Year Failure To Stop Harassment. BuzzFeed News. https://www.buzzfeednews.com/article/charliewarzel/a-honeypot-for-assholes-inside-twitters-10-year-failure-to-s#.hmXK9n25
Williamson, D. (2020, June 2). US Social Media Usage: How the Coronavirus is changing consumer behavior. eMarketer. https://www.emarketer.com/content/us-social-media-usage