Despite heightened awareness of the detrimental impact of hate speech on social media platforms on affected communities and public discourse, there is little consensus on approaches to mitigate it. While content moderation—either by governments or social media companies—can curb online hostility, such policies may suppress valuable as well as illicit speech and might disperse rather than reduce hate speech. As an alternative strategy, an increasing number of international and nongovernmental organizations (I/NGOs) are employing counterspeech to confront and reduce online hate speech. 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.

尽管人们对社交媒体平台上的仇恨言论对受影响社区和公共话语的有害影响有了更高的认识，但在缓解它的方法上几乎没有达成共识。虽然内容节制——无论是政府还是社交媒体公司——可以遏制在线敌意，但此类政策可能会压制有价值的言论和非法言论，并且可能会分散而不是减少仇恨言论。作为一种替代策略，越来越多的国际和非政府组织 (I/NGO) 正在使用反言论来对抗和减少在线仇恨言论。尽管它们越来越受欢迎，但关于反演策略的有效性和设计（在公共领域）的实验证据很少。模拟我们对当前 I/NGO 实践的干预，我们将发送过包含仇外（或种族主义）仇恨言论的信息的说英语的 Twitter 用户随机分配到三种反驳策略（同理心、后果警告和幽默）之一或对照组。我们对 1,350 名 Twitter 用户的意向治疗分析表明，基于同理心的反驳信息可以将仇外仇恨言论的回顾性删除增加 0.2 SD，并在 4 周的随访期内将仇外仇恨言论的预期创建减少 0.1标清。然而，我们发现使用幽默或后果警告的策略没有一致的效果。总之，这些结果促进了我们对同理心在减少排斥行为中的核心作用的理解，并为未来反言干预的设计提供了信息。