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When you think about what’s controlling your emotions, you may naturally assume that the forces come from within you or at least from those with whom you interact on a daily basis. You’re in a good mood because you’ve just finished an important project, cooked a delicious meal, or had fun with your friends or family.
As you turn to your online news feed, though, your mood suddenly takes a nosedive. One of your favorite celebrities is going through a messy breakup and you somehow feel betrayed. You thought that relationship was rock solid but now, with the breakup, you realize that it’s been coming apart for years.
The newsfeed may also have more direct implications for your own life when the information causes you to feel personally threatened. The spread of the coronavirus to pandemic proportions in 2020 is one particularly severe example. Not only are people afraid of the disease itself, but also of its many real-life ramifications. The shortages of toilet paper in the U.S. along with other necessities is a direct result of such feelings of perceived threat.
In a newly published paper, Harvard University’s Amit Goldenberg and Stanford University’s James Gross examine this phenomenon—what they refer to as “digital emotion contagion.” In general, emotion contagion is defined as “the process by which the emotions of a perceiver become more similar to those of others as a result of exposure to these emotions” (p. 317). In digital emotion contagion, your emotions become more like those of other people whose posted messages contain content with an affective flavor.
This idea of digital emotion contagion may seem familiar if you recall the 2014 uproar over an online experiment in which Facebook feeds were experimentally manipulated to produce positive or negative emotions in millions of unknowing users. Even so, the manipulation of your mood by online postings continues, Goldenberg and Gross note, from online social awareness movements to posts by people you know who share their current psychological states.
As the authors conclude, “Given the tremendous exposure to the emotions of others on digital media, the contagious spread of digital emotions seems to be having a powerful impact on user emotions and behavior” (p. 316).
Although the explanation of digital emotion contagion may seem perfectly obvious to you (i.e., you become sad when others become sad), the Harvard-Stanford researchers believe the explanation is more complex than this. As they note, contagion can occur through three possible cognitive and social mechanisms.
In simple mimicry, you just copy another person’s expression of emotions through the face, bodily movements, and tears or laughter. Online, this would amount to repeating the words of someone in your social network in your own posts, possibly sprinkled with emojis.
The second process is category activation, a cognitive mechanism that occurs when you encounter an emotional word that applies to a particular group of feeling states (such as sadness). This exposure primes you mentally for other related words (such as sorrowful).
Third, social appraisal may cause you literally to experience the emotions of others. You see or read about their emotional state and use this as a guide for how you should be feeling. After all, if other people are feeling panicky, then perhaps you shouldn’t feel happy after all, even if things are going relatively well for you in your personal life.
It’s possible for all three of these processes to work together. Perhaps you haven’t had a good day so far at all and you’re seeking some distractions. You go to one of your favorite online forums when one of the participants shares an amusing anecdote about a cat getting stuck in (but then rescued from) the top of a tall cabinet. You share in the virtual laughter of the others in the group and, at least for the moment, feel some relief. In part, you can attribute this to the fact that you’ve just had a giggle or two (mimicry) and to the words used to describe the pet’s predicament (category activation), but it also helps that the post received a decent number of likes as well as those accompanying emojis (social appraisal).
Digital emotion contagion may have its theoretical place in psychology, but there is a dark side to the phenomenon as well. The emotions you feel in response to the posts in your feed, according to Goldenberg and Gross, are exactly the reactions the companies who control social media try to promote. Emotional connections keep users engaged, and engagement translates into activity which ultimately translates into advertising dollars. These companies, the authors further argue, try to promote digital emotion contagion by incentivizing competition for the kind of attention that comes from likes, shares, and retweets.
Because positive emotions are more likely to be shared and liked than negative ones, these companies wish to shape the behavior of users so that they more frequently express happiness, humor, and affection (think that cat on the cabinet). To test this theory, the authors downloaded over 1.5 million random tweets, assigning numerical ratings based on the emotion the tweets expressed. Their analysis graphically showed that as the emotional content went from negative to positive, passing through neutral along the way, both indicators of user reactions gained exponentially.
Exceptions to the positive emotion rule do occur, however, as in the case of anger. You’ve probably witnessed this yourself when the trends in your news feed attempt to incite users into social action. In the words of the authors, “Users are also motivated to share their anger because they wish to signal their social network about their [own] morality and to convince them to join the movement” (p. 320). This is how your good mood can be reversed by a rant gone viral. However, online anger rarely translates into sustained activity in the real world, as shown by studies of the enduring effects of posts intended to raise money for a good cause (e.g. the "ice bucket" challenge for ALS).
As much as people become emotionally aroused through online interactions, however, there can be a point at which users reach habituation or fatigue. You might be able to relate to this if you’ve decided to get off all social media during difficult political or economic times. You’re tired of seeing the trends that emphasize all the problems in the world, so you vow to take a break. Should you happen to sneak a peek at one of your feeds, that emotional content continues to rage on, but you’ve been able to immunize yourself to its effects. Goldenberg and Gross note that you might even share the content, retaining its emotional meaning, but you don’t actually experience the emotion it’s expressing.
Furthermore, unlike emotions that play out in a face-to-face setting, you can actually inhibit an online reaction to emotion-based content by waiting until you calm down, a strategy you may have developed from a comment you posted that you later regretted. For this reason, as Goldenberg and Gross observe, the asynchronous nature of online interactions creates problems in studies on digital emotion contagion, meaning that the emotional effects cannot clearly be examined through studies of user posts.
The purpose of the paper was to lay out the main issues facing the emerging field of digital emotion contagion as well as to suggest possible underlying cognitive mechanisms. From the standpoint of users, it seems clear that without realizing it, your emotions are being manipulated by the digital powers that be. Even though there is a tendency for positive emotions to produce larger responses across a social media platform, some fear-producing messages can take on a viral quality of their own.
To sum up, there can be many fulfilling aspects of social media use, particularly if you’re seeking some escape from daily life. To maintain that fulfillment, remember that you can be in control of your own emotions once you recognize that you are.
Facebook image: Fizkes/Shutterstock
LinkedIn image: Eakkaluktemwanich/Shutterstock
References
Goldenberg, A., & Gross, J. J. (2020). Digital emotion contagion. Trends in Cognitive Sciences. doi: 10.1016/j.tics.2020.01.009
