Models reveal how hostile online speech unfolds around social groups
Unifying Models of Intergroup Hostility in Online Discourse
Computation and LanguageSocial and Information Networks
Summary
Hostile language online can lead to more division and mistreatment of social groups. The authors looked at nearly 3 million posts on TikTok, Truth Social, and Twitter to study six ways hostility happens in real chats. They found that certain ideas, like deciding who belongs in a group and seeing others as threats, appear early and shape how people talk. This helps combine different social science ideas into a clearer picture of how online hostility works.
What this means in practice
- •For social media moderators: Identify early signs of hostile group rhetoric to improve content moderation systems during political events.
- •For online community managers: Design better interventions by understanding the order and role of hostile speech patterns in group interactions.
Authors
Patrick Gerard, Julia Mendelsohn, Kristina Lerman
Abstract
Hostile rhetoric toward social groups can normalize exclusion and justify mistreatment, as well as contribute to rising polarization and political violence. Efforts to moderate hostile rhetoric in online speech draw on foundational theories in social and moral psychology, and political science. However, these theories were developed largely in parallel, often propose different and sometimes conflicting accounts of how hostility develops, and have rarely been tested against each other in real discourse. The result is a fragmented understanding of the rhetorical mechanisms of hostility, without a clear sense of how they appear, and relate to each other, in real-world discourse. Using 2.86 million posts from TikTok, Truth Social, and Twitter/X during the 2024 U.S. presidential election, we model the mechanisms of six foundational theories of intergroup hostility -- boundary construction, threat construction, scapegoating, negative evaluation, dehumanization, and action orientation -- within a common empirical framework to recover the broader organization of intergroup hostility rhetoric. Structurally, we find that boundary construction and threat construction anchor the system; temporally, we find that these mechanisms tend to follow a regular ordering: boundary construction, derogation, and action orientation tend to appear early; dehumanization and threat construction later; scapegoating latest. Mapping how these theoretical frameworks actually manifest in discourse bridges longstanding divisions across social science traditions and presents computational social science with a clearer empirical foundation for modeling intergroup hostility rhetoric beyond single-label detection.