Perceiving and Countering Hate: The Role of Identity in Online Responses

Abstract

This study investigates how online counterspeech, defined as direct responses to harmful online content with the intention of dissuading the perpetrator from further engaging in such behavior, is influenced by the match between a target of the hate speech and a counterspeech writer's identity. Using a sample of 458 English-speaking adults who responded to online hate speech posts covering race, gender, religion, sexual orientation, and disability status, our research reveals that the match between a hate post's topic and a counter-speaker's identity (topic-identity match, or TIM) shapes perceptions of hatefulness and experiences with counterspeech writing. Specifically, TIM significantly increases the perceived hatefulness of posts related to race and sexual orientation. TIM generally boosts counter-speakers' satisfaction and perceived effectiveness of their responses, and reduces the difficulty of crafting them, with an exception of gender-focused hate speech. In addition, counterspeech that displayed more empathy, was longer, had a more positive tone, and was associated with higher ratings of effectiveness and perceptions of hatefulness. Prior experience with, and openness to AI writing assistance tools like ChatGPT, correlate negatively with perceived difficulty in writing online counterspeech. Overall, this study contributes insights into linguistic and identity-related factors shaping counterspeech on social media. The findings inform the development of supportive technologies and moderation strategies for promoting effective responses to online hate.

Figures (3)

• Figure 1: A Two-Level Hierarchical Study of Counterspeech. The figure shows the data structure of our study, where counterspeech responses are nested within participants. Each participant responded to three random hate posts, each with a different topic (race, religion, gender, disability, or sexual orientation).
• Figure 2: Estimated Marginal Means Analysis of Perceived Hatefulness Ratings by TIM. The figure shows the marginal mean ratings of the counterspeech writers on five topics: religion, race, gender, sexual orientation, and disability. The error bars represent the 95% confidence intervals. Asterisks indicate levels of significance: *$P < .05$, **$P < .01$, and ***$P < .001$. Across all topics, hate posts were perceived as significantly more hateful when there was a TIM compared to when there was none ($P=.001$). Hate speech targeting race and sexual orientation was perceived as significantly more hateful compared to hate speech targeting disability, gender, and religion ($P<.001$).
• Figure 3: Perceived Difficulty of Writing Counterspeech by ChatGPT Usage Experience. We compare the perceived difficulty of writing counterspeech between participants with and without prior ChatGPT experience. The orange bars represent the prior use of ChatGPT group, and the blue bars represent the no ChatGPT experience group. Asterisks indicate levels of significance: *$P < .05$, **$P < .01$, and ***$P < .001$. The bars are labeled with the mean values of the perceived difficulty with 95% confidence intervals. Analysis reveals two significant relationships: (1) Participants with prior ChatGPT experience report lower difficulty in writing counterspeech compared to those without experience ($P = .039$), and (2) Among participants who rate ChatGPT as moderately to extremely useful, those who perceive it as more useful report significantly lower difficulty in writing counterspeech ($P < .001$).