Outgroup Animosity Drives Engagement on Social Media


There has been growing concern about the role social media plays in political polarization. We investigated whether outgroup 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 outgroup were shared or retweeted about twice as often as posts about the ingroup. Each individual term referring to the political outgroup increased the odds of a social media post being shared by 67%. Outgroup language consistently emerged as the strongest predictor of shares and retweets: the average effect size of outgroup 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. Language about the outgroup was a very strong predictor of “angry” reactions (the most popular reactions across all datasets), and language about the ingroup was a strong predictor of “love” reactions, reflecting ingroup favoritism and outgroup derogation. This outgroup effect was not moderated by political orientation or social media platform, but stronger effects were found among political leaders than among news media accounts. In sum, outgroup 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 outgroup animosity.

Proceedings of the National Academy of Sciences