Rathje, Van Bavel & Van der Linden (2021) — Out-group animosity drives engagement on social media
Rathje, S., Van Bavel, J.J. & Van der Linden, S. (2021). Out-group animosity drives engagement on social media. Proceedings of the National Academy of Sciences, 118(26), e2024292118. https://doi.org/10.1073/pnas.2024292118
What this source contributes
Large-scale analysis of 2,730,215 posts from news media accounts and US congressional members on Facebook and Twitter. Key finding, verbatim from the abstract: “Posts about the political out-group were shared or retweeted about twice as often as posts about the in-group. Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%.”
Language referring to the opposing political side was the strongest predictor of sharing in the dataset: the 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. The study isolates which signal spreads hardest — not anger in general, but hostility directed at a political opponent.
Analytical function in Ragebaiting
Where Brady et al. (2017) establishes that moral-emotional language spreads, Rathje et al. (2021) sharpens the mechanism to its most reliable form: attacks on the opposing political camp. This is the finding that explains targeting — why ragebait-for-revenue networks aim their fabricated outrage at migrants, asylum seekers, and politicians rather than at random provocations. Those are the most dependable engagement targets, and the same paper is cited by Justice for Prosperity (2026) as the empirical basis for the revenue-model networks it maps.
The out-group animosity finding is the bridge between the abstract claim that “anger spreads” and the concrete observation that the anger almost always points the same way.
Related entries
- Ragebaiting — the designed deployment of out-group animosity as an engagement strategy