How Do Those Who Post Hate Speech Respond to Different Counter-speech Strategies?

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Authors: Yue Jia, Kristine Hansen, Tiago Garrido Marques, Sandy Schumann, Zoe Wei
Cited by: 0

Abstract

Hate speech flourishes online. In addition to the (automated) detection and removal of hate, counter-speech has been proposed as a measure to address this harm. To date, however, it remains unclear what counter-speech strategies predict changes in the behaviour of those who express hate online. Advancing the literature, we conducted a content analysis of N = 3,907 hate speech posts on X, which targeted different outgroups, and N = 5,428 subsequent comments, including counter-speech and reactions of those who had posted hate. First, we sought to determine the prevalence of five types of counter-speech (e.g., attacking the perpetrator, off-topic comments, sharing facts that discount the perpetrator’s rationale). Second, we aimed to explore which counter-speech strategy was associated with a higher likelihood of apologies or less hateful expressions rather than persistent hate speech. Findings showed that almost half of the hate speech posts received no responses. When comments were added to hate speech, these were in almost one-third of all cases endorsing hate. The remaining replies were predominantly off-topic/ diversionary; the least common counter-speech strategy was to evoke empathy with the hate speech victim(s). Those who posted hate speech did typically not react to either of the responses within the same conversation thread. Eleven percent continued to post hate and eleven percent reduced their hateful expressions or even apologised, respectively. The likelihood of the latter was elevated when counter-speech aimed to evoke empathy with the victim. We discuss this result considering previous research on parochial empathy.

Fields of Study & Subjects

Hate Speech and Cyberbullying Detection Bullying Victimization and Aggression Misinformation and Its Impacts

Publication details

Journal / source
CrimRxiv
Publication date
10 January 2026
Language
EN
Document type
Preprint