Empathy-based counterspeech can reduce racist hate speech in a social media field experiment

Abstract

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.

Towards Automatic Generation of Messages Countering Online Hate Speech and Microaggressions

“…The counternarrative has been studied as a means of confronting hate speech. Many researchers report that counternarratives are effective for reducing hate online (Hangartner et al, 2021). Several NGOs, such as Dangerous Speech Project 2 , are working to promote counterspeech, and social networking platforms are also encouraging the use of counterspeech.…”

ProsocialDialog: A Prosocial Backbone for Conversational Agents

“…( 2) Base feedback on empathy: when pushing back, there are several types of effective counter speech, such as showing empathy, warning the consequence, and incorporating humor (Benesch et al, 2016). Recent experiments show that combining empathy is the most effective among those in reducing hate speech (Hangartner et al, 2021). ( 3) Show how to change: constructive feedback should also suggest better alternative behavior rather than pointing out the wrongs only (Hattie and Timperley, 2007).…”

Personalized Interventions for Online Moderation

“…Each user could be described in terms of its social and personality profile [14], including its social vulnerabilities [27]. The former characteristics are linked to the emergence of online misbehavior [16], while the latter are linked to the effectiveness of a given intervention for a given user [2,10]. Knowledge of such individual characteristics is instrumental in the development of effective PMIs.…”