During the last fifteen years, social media has evolved in ways most of us could not have predicted. So many people, myself included, engage with social media platforms on a daily basis. Often times, we go without asking ourselves if this frequent usage may have lasting impacts on our mental, emotional, or even physical wellbeing. And with the introduction of targeted algorithms, we are seeing a positive correlation with a rise in mental health concerns related to social media usage. Targeted algorithms are defined by the MIT Schwarzman College of Computing as algorithms designed with intent to “predict or anticipate the needs and behaviors of individuals and audiences”.
When Facebook was first introduced, its founders were looking for a way to gage and influence user traffic. In 2009, Facebook became the first social media platform to use algorithms and user analytics to improve engagement outcomes. With the introduction of an algorithm called EdgeRank, Facebook was a pioneer in targeted algorithm usage.
EdgeRank attempted, rather successfully, to sort the feeds of Facebook users by relevance. The algorithm uses a specific formula to determine which media (articles, memes, friends posts, etc.) should be displayed first on a users feed. The EdgeRank algorithm has since been replaced with a machine learning tool.
The underlying goal with algorithms such as EdgeRank is very simple—to increase user engagement and to keep users engaged for longer. And once the algorithms’ effectiveness was established, other social media platforms were quick to follow suit.
Instagram co-founder Kevin Systrom told the New York Times, while discussing targeted algorithms, “On average, people miss about 70 percent of the posts in their Instagram feed,” he continued, “What this is about is making sure that the 30 percent you see is the best 30 percent possible.”
But, what is the “best” in this context? In many ways, I think it is likely that the co-founder of Instagram is speaking almost exclusively from a perspective of user engagement rather than user experience. User engagement ensures that users are staying on a platform longer, but is not necessarily focused on whether the content being displayed is positive or negative. User experience takes into account how users are feeling towards the content they are being shown.
If we are being shown content that is specifically intended to promote user engagement, we may be exposed to content that we otherwise wouldn’t seek out on our own, or content that we do not want to be seeing, but can’t look away from either.
Many psychologists are now likening excessive social media usage to addiction. Social media offers stimulation to our brains, and over time, we become increasingly dependent on that stimulation and have a difficult time controlling our social media usage because of it.
In addition to the addictive aspects of social media, it is often attributed to a recent increase in depression. The Royal Society for Public Health, & Young Health Movement (2017) reports that diagnoses of depression and anxiety have increased by 70% within the past twenty five years. Some speculate that the prevalence of social media usage should be considered as a factor. The Pew Research Centre (2015) reports that a staggering 92% of teenagers and adolescents are active on some social media platform.
These issues are often linked to social media for many reasons, but maybe mainly because it offers constant exposure to the lives of others, and some may feel pressure to live up to unrealistic expectations. And when combined with targeted algorithms, this constant exposure may feel inescapable.
Another common complaint of social media is that it could be making us all more narcissistic. However, it is important to keep social norms in consideration. If every one around us is doing something, we are less likely to view the behavior as being harmful or negative, such as taking selfies and uploading them to social media on a regular basis. Again, social media algorithms can magnify this effect. And in this case, those who choose not to post may be ostracized for not participating in established social norms. Teenagers and adolescents are particularly vulnerable in situations like this.
Social media platforms such as Facebook and Instagram are now recognized as two of the largest social media platforms in the world, with Facebook alone reaching nearly 3 billion users per month. Their priority is likely to keep engagement steady for the foreseeable future, which is aided by targeted algorithms.
Facebook and Instagram, as well as many other major social media platforms, gather all sorts of data on their users to help determine which media would best fit each individual. This data is used to run specific algorithms that are catered toward your preferences, likes and dislikes, political leanings, and much more.
This data, for many people could be considered very private, and some may not realize that such extensive personal information is being collected. This could introduce another aspect of mental harm perpetuated by social media platforms.
The analytics of social media use are also important to understanding how these platforms run. Social media analytics are most interested in “facilitating conversations and interaction between online communities, and
extracting useful patterns and intelligence to serve entities that include, but are not limited to, active contributors in ongoing dialogue” (Zeng, et al).
It has been made increasingly apparent that more attention should be paid to the power of social media algorithms. The companies at the head of this issue should be held to some standard of accountability and disclose their practices more openly.
Works Cited
Kumar, S., Zafarani, R., & Liu, H. (2011). Understanding User Migration Patterns in Social Media. Proceedings of the AAAI Conference on Artificial Intelligence, 25(1), 1204-1209.
Betul Keles, Niall McCrae & Annmarie Grealish (2020) A systematic review: the influence of social media on depression, anxiety and psychological distress in adolescents, International Journal of Adolescence and Youth, 25:1, 79-93
Isaac, M. (2016, March 15). Instagram may change your feed, personalizing it with an algorithm. The New York Times. https://www.nytimes.com/2016/03/16/technology/instagram-feed.html?_r=0
EdgeRank.” Wikipedia, Wikimedia Foundation, 4 Oct. 2022, https://en.m.wikipedia.org/wiki/EdgeRank.
D. Zeng, H. Chen, R. Lusch and S. -H. Li, “Social Media Analytics and Intelligence,” in IEEE Intelligent Systems, vol. 25, no. 6, pp. 13-16, Nov.-Dec. 2010, doi: 10.1109/MIS.2010.151.
Franziska Zimmer, Katrin Scheibe, Mechtild Stock, Wolfgang G Stock
Journal of Information Science Theory and Practice 7 (2), 40-53, 2019
“The Latest Facebook Statistics: Everything You Need to Know – Datareportal – Global Digital Insights.” DataReportal, https://datareportal.com/essential-facebook-stats.