Political polarization has been growing rapidly in the United States over the past few decades. In polarized political contexts, out-group animosity may be a more successful strategy for expressing one’s partisan identity and generating engaging content than in-group favoritism. There is already evidence suggesting that people selectively follow ( 41) and retweet ( 10, 42) in-group members at much higher rates than out-group members. Accordingly, we suggest that just as people engage in motivated cognition-processing information in a way that supports their beliefs-people may also engage in motivated tweeting (or sharing, liking, or retweeting), selectively interacting with and attending to content that aligns with their partisan identity motivations. Partisan motivations have been hypothesized to influence online behavior, such as the sharing of true and false news online ( 39, 40). Scholars noted early on that the degree to which individuals identify with their political party “raises a perceptual screen through which the individual tends to see what is favorable to his partisan orientation” ( 38). People may process information in a manner that is consistent with their partisan identities, prior beliefs, and motivations, a process known as motivated cognition ( 34– 37). As an anecdotal example, executives at the website Buzzfeed, which specializes in creating viral content, reportedly noticed that identity-related content contributed to virality and began creating articles appealing to specific group identities ( 33). Thus, messages that fulfill group-based identity motives may receive more engagement online. According to social identity theory ( 30) and self-categorization theory ( 31), when group identities are highly salient, this can lead individuals to align themselves more with their fellow in-group members, facilitating in-group favoritism and out-group derogation in order to maintain a positive sense of group distinctiveness ( 32). Additionally, since sharing behavior is public, it can reflect self-conscious identity presentation ( 28, 29). For example, an analysis of Twitter accounts found that people are increasingly categorizing themselves by their political identities in their Twitter bios over time, providing a public signal of their social identity ( 27). Group identities are hypersalient on social media, especially in the context of online political or moral discussions ( 26).

Yet, to our knowledge, little research has investigated how social identity motives contribute to online virality. 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. This out-group effect was not moderated by political orientation or social media platform, but stronger effects were found among political leaders than among news media accounts.

Language about the out-group was a very strong predictor of “angry” reactions (the most popular reactions across all datasets), and language about the in-group was a strong predictor of “love” reactions, reflecting in-group favoritism and out-group derogation. Out-group language consistently emerged as the strongest predictor of shares and retweets: the average effect size of out-group language was about 4.8 times as strong as that of negative affect language and about 6.7 times as strong as that of moral-emotional language-both established predictors of social media engagement. Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%. 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 in-group. We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. There has been growing concern about the role social media plays in political polarization.

Cult animosity no sign letting up