Ingroup bias is prevalent in user reports of hate and abuse online

Abstract

The prevalence of online hate and abuse is a pressing global problem. While tackling such societal harms is a priority for research across the social sciences, it is a difficult task, in part because of the magnitude of the problem. People's engagement with reporting mechanisms ('flagging') online is an increasingly important part of monitoring and addressing harmful content at scale. However, users may not flag content routinely enough, and when users do engage, they may be biased by group identity and political beliefs. Across five well-powered and pre-registered online experiments, we examine the extent of ingroup bias in people's flagging of hate and abuse in four different intergroup contexts: political affiliation, vaccination opinions, beliefs about climate change, and stance on abortion rights. Overall, participants reported abuse reliably, with approximately half of the abusive comments in each study reported. However, a pervasive ingroup bias was present whereby across studies, participants were between 17% and 63% more likely to flag abuse directed at the ingroup than at the outgroup. Our findings offer new insights into the nature of user flagging online, an understanding of which is crucial for enhancing user intervention against online hate and thus ensuring a safer online environment.

Accepted for publication in Royal Society Open Science (June 2026). This is the accepted manuscript prior to copyediting and typesetting