mlsanityData to 7 Oct 2026

Hatred Stems from Ignorance! Distillation of the Persuasion Modes in Countering Conversational Hate Speech

arXiv 2403.15449 ↗First posted 18 Mar 2024cs.CL cs.AIcited by 2

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Abstract (arXiv)

Examining the factors that the counterspeech uses are at the core of understanding the optimal methods for confronting hate speech online. Various studies have assessed the emotional base factors used in counter speech, such as emotional empathy, offensiveness, and hostility. To better understand the counterspeech used in conversations, this study distills persuasion modes into reason, emotion, and credibility and evaluates their use in two types of conversation interactions: closed (multi-turn) and open (single-turn) concerning racism, sexism, and religious bigotry. The evaluation covers the distinct behaviors seen with human-sourced as opposed to machine-generated counterspeech. It also assesses the interplay between the stance taken and the mode of persuasion seen in the counterspeech. Notably, we observe nuanced differences in the counterspeech persuasion modes used in open and closed interactions, especially in terms of the topic, with a general tendency to use reason as a persuasion mode to express the counterpoint to hate comments. The machine-generated counterspeech tends to exhibit an emotional persuasion mode, while human counters lean toward reason. Furthermore, our study shows that reason tends to obtain more supportive replies than other persuasion modes. The findings highlight the potential for incorporating persuasion modes into studies about countering hate speech, as they can serve as an optimal means of explainability and pave the way for the further adoption of the reply's stance and the role it plays in assessing what comprises the optimal counterspeech.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 20 of its 68 references that are in the map. First posted on arXiv 18 Mar 2024.

Builds on

20 of 68 references.

References · 20

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8 more
  1. 2023Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Languagecited by 22
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2 papers.