Your Instagram Told Me So…
Social media data is being analyzed to measure employee engagement and to preempt dangerous student behavior. Should it be used to predict mental illness?
Researchers at IBM found that engagement levels of employees may be inferred from their word choices in social media posts (1). Meanwhile, in his article in Wired, Tim Simonite sheds light on the current debate surrounding the efficacy and ethics of academic institutions monitoring student social media posts to prevent tragedies such as school shootings (2). As social media monitoring continues and the applicability of such monitoring is explored, a likely complement will be the heightened attention to mental health exhibited today by employers and academic institutions alike.
Social media data has been repeatedly used to predict mental illnesses like depression (3, 4). I find it likely that these findings will trickle into what employers and schools are looking at in their existing use of social media data. I predict we will soon see employers and academic institutions using social media data to predict the prevalence of mental illness among their employees and students, just as they are doing so to measure engagement levels and preempt dangerous behavior. I would like to express a view of caution against this notion. While I celebrate the increased care that society is broadly taking toward mental wellness, I am concerned for the implications of using analytics surrounding social media to take such care.
First, my concerns regarding social media analytics to monitor and measure mental health stem from the fact that social media use has been linked to diminished levels of psychological well-being (5). If employers and academic institutions introduce the monitoring of their employees’ and students’ social media as part of their measures to care for their mental health (whether or not the subjects of the monitoring are made aware of it), will this result in an encouragement by these organizations for increased use of social media for the sake of robust data sets? If social media data were used to predict mental illness, it would likely be used in tandem with mental health initiatives aimed at improving mental well-being as a way to measure the efficacy of these initiatives. However, any encouragement or prompting of social media use on behalf of these organizations could very well exacerbate the issues they would be aiming to abate.
Second, I worry for what I predict could be an over-reliance on social media analytics to monitor concerns as nuanced and important as mental health. Consider the nature of social media as a manifestation of an individual’s mental state as compared to data sources such as surveys or network data. There’s an argument to be made that social media data, given its informal tone and fostering of free-form self expression, might offer more accurate insights into an individual’s mental health than do formal surveys or measurements of the frequency of an individual’s interactions with others. However, I argue that social media data in fact trends in the opposite direction, away from accuracy. Social media introduces another layer that stands between an individual’s true mental state and the way it is captured in data. This layer consists of the careful curation, presentation, and social comparison that are all at play when a person posts on social media. These elements are also what an individual, whether deliberately or subconsciously, may use to present what is specifically an inaccurate depiction of their own well-being. It is an unfortunate cliche of our time that an unhappy person will use social media to feign happiness. Even if a sophisticated algorithm were able to capture such deceit, what about the element of curation? If individuals choose only to publicize truly positive moments or sentiments on social media and refrain from posting anything negative, would an algorithm detect such absent content? We can again give an algorithm the benefit of the doubt in terms of sophistication, and trust that it would be able to predict mental illness using word choice in any kind of social media posting, be it explicitly positive, negative, or neutral in tone. Still, there is further nuance to acknowledge in that a person might change their levels of engagement with social media depending on their mental state, preventing any data collection from capturing a full and accurate picture. All of this is to say that, with a concern like mental health, it will not be enough for organizations like employers or schools to monitor social media and trust that they have the full picture. Social media analytics must not become a box that organizations can check off and move on from. With mental health and mental illness, employers and academic institutions owe it to their employees and students to be many-model thinkers.
(1) Inferring Employee Engagement from Social Media, https://dl.acm.org/doi/abs/10.1145/2702123.2702445
(2) Schools Are Mining Students’ Social Media Posts for Signs of Trouble, https://www.wired.com/story/algorithms-monitor-student-social-media-posts/
(3) Multi-Kernel SVM Based Depression Recognition Using Social Media Data, https://link.springer.com/article/10.1007/s13042-017-0697-1
(4) Detecting Depression and Mental Illness on Social Media: An Integrative Review, https://wwbp.org/papers/detecting_depression_twitter_2017.pdf
(5) Media Use Is Linked to Lower Psychological Well-Being: Evidence from Three Datasets, https://link.springer.com/article/10.1007/s11126-019-09630-7
Very interesting topic, thank you for sharing it! I agree with your comment about cliche that the depressed person is likely to look for happiness in the social media. Depression can take many forms and differs in severity, that might result in statistically significant difference in behavior on social media platforms. Then, again, abnormality of any behavior on Facebook or Instagram might be caused by some other factors, such as new job, new life situation or just being bored at home on quarantine.
Super interesting! Very insightful that you’re predicting the use of social media to track employee well-being based on trends in education. I agree with this assessment, particularly given that it’s already being used to a certain extent in hiring. I agree that social media is highly curated and a challenging source of accurate information. However, aside from the highly curated environment, just question whether companies should use data from employees on what is supposed to be a private platform. I understand that people can use to make their profile public or private, and choose what they want to post know their employer might see it, but there is a reason why boundaries are drawn between work and life. I don’t need my company knowing what I do on weeknights and the weekend or how I’m feeling about it. That business should be left up to me.
Very relevant topic! I wonder if social media companies would support these practices or not. If they viewed this behavior as having negative repercussions for their platform, they may implement policies that specifically prohibit this practice. The more concerning side of this is if social media companies view these practices favorably and invest in making it easier for employers and schools to access and analyze data.
Thanks for sharing, Jade! Super interesting topic – especially as we will presumably see engagement with social media increase while under quarantine. I wonder how institutions would choose to implement such a strategy. For example, would they require students or employees to give them access to their profiles so that they could run their algorithms? Additionally, if an algorithm is eventually developed to accurately predict serious issues like depression, is it the responsibility of an employer to identify those traits? Or should the social media platforms themselves take on that responsibility?
While I too appreciate the intentions of employers and schools who are trying to attend to employees’ and students’ mental health, I agree that resources may be better spent investing in other initiatives. I absolutely agree that individuals present a curated version of themselves on social media, and it may be futile to try to understand an individual’s emotional state based exclusively on their social media presence. I imagine that a 10-minute conversation with an employee or student would be a lot more informative than a glimpse of someone’s Instagram, for example.
Furthermore, even if employers could successfully deduce an individual’s mental health state from social media posts, I am not sure it would be appropriate for my employer to initiate a conversation about my mental health based on observations of my behavior outside of the work context.
Jade! Super interesting article! Two topics I really like discussing combined in one article. I agree with your views on the curation point on social media and have grappled with the choice that people have in engaging with these platforms. There is an argument to be made that there is positive content to prevent negative feelings so wide spread on the internet and therefore, I question whether employers using this as the sole tool for analyzing mental health is the right form of measure. It could be most certain one data input and be supplemented with the flagging of extremely positive or negative data being flagged as you suggested and then following up with the employee with some questionnaire to ask questions to fortify the data collected from social media. I cannot speak for everyone but I do see social media as an outlet for creativity and also a way to be connected and therefore elements of the content can provide insights for those parameters! Exited to see how companies tackle this!