Despite their growing popularity, there is scant experimental evidence on the effectiveness and design of counterspeech strategies (in the public domain). Modeling our interventions on current I/NGO practice, we randomly assign English-speaking Twitter users who have sent messages containing xenophobic (or racist) hate speech to one of three counterspeech strategies—empathy, warning of consequences, and humor—or a control group. Our intention-to-treat analysis of 1,350 Twitter users shows that empathy-based counterspeech messages can increase the retrospective deletion of xenophobic hate speech by 0.2 SD and reduce the prospective creation of xenophobic hate speech over a 4-wk follow-up period by 0.1 SD. We find, however, no consistent effects for strategies using humor or warning of consequences. Together, these results advance our understanding of the central role of empathy in reducing exclusionary behavior and inform the design of future counterspeech interventions.https://scite.ai/reports/empathy-based-counterspeech-can-reduce-racist-3nbAEbz2Share this:FacebookXLike this:Like Loading... Post navigation New approaches to combatting online hate speech (Gilbert & Tobin Law) Conscious or Unconscious: The Intention of Hate Speech in Cyberworld—A Conceptual Paper (MDPI)