misinformation, and appeal to people’s existing biases and preferences. 1 2 [T]he problem is that when we encounter opposing views in the age and context of social media, it’s not like reading them in a newspaper while sitting alone. It’s like hearing them from the opposing team while sitting with our fellow fans in a football stadium. Online, we’re connected with our communities, and we seek approval from our like-minded peers. We bond with our team by yelling at the fans of the other one. In sociology terms, we strengthen our feeling of “in-group” belonging by increasing our distance from and tension with the “out-group”—us versus them…. This is why the various projects for fact-checking claims in the news, while valuable, don’t convince people. Belonging is stronger than facts.26 3 4 5 6 7 8 50. 9 A study published in June 2021 showed that posts attacking “others” (the “out- group”) are particularly effective at generating social rewards, such as likes, shares, and 10 comments, and that those reactions consist largely of expressions of anger: 11 We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts and US congressional members (n = 2,730,215), we found that posts about the political out-group were shared or retweeted about twice as often as posts about the ingroup.… Out-group language consistently emerged as the strongest predictor of shares and retweets…. Language about the out-group was a very strong predictor of “angry” reactions (the most popular reactions across all datasets)…. In sum, out-group language is the strongest predictor of social media engagement across all relevant predictors measured, suggesting that social media may be creating perverse incentives for content expressing out-group animosity.27 12 13 14 15 16 17 18 51. 19 20 21 22 Another study, published in August 2021, analyzed how “quantifiable social feedback (in the form of ‘likes’ and ‘shares’)” affected the amount of “moral outrage” expressed in subsequent posts. The authors “found that daily outrage expression was significantly and positively associated with the amount of social feedback received for the previous day’s outrage expression.” The amount of social feedback is, in turn, determined by the algorithms underlying 23 the social media product: 24 25 26 26 Zeynep Tufekci, How social media took us from Tahrir Square to Donald Trump, MIT TECHNOLOGY REVIEW (Aug. 14, 2018), https://technologyreview.com/2018/08/14/240325/howsocial-media-took-us-from-tahrir-square-to-donald-trump. 27 27 28 Steve Rathje, Jay J. Van Bagel, Sander van der Linden, Out-group animosity drives engagement on social media, 118 PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES (26), (June 29, 2021), https://doi.org/10.1073/pnas.2024292118. CLASS ACTION COMPLAINT 18 Case No. __________________