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.

翻译：本研究探讨了网络对抗性言论——即针对有害网络内容、意图劝阻施害者继续此类行为的直接回应——如何受到仇恨言论目标与对抗性言论作者身份匹配度的影响。通过对458名英语成年人的样本分析，这些受试者回应了涉及种族、性别、宗教、性取向及残障状况的网络仇恨言论帖子，我们的研究表明：仇恨帖文的主题与对抗性发言者身份的匹配度（主题-身份匹配，简称TIM）会影响对仇恨程度的感知及对抗性言论撰写的体验。具体而言，TIM显著提升了针对种族和性取向相关帖文的仇恨感知度。除性别类仇恨言论外，TIM普遍增强了对抗性发言者的满意度、对其回应有效性的感知，并降低了撰写难度。此外，展现更多同理心、篇幅更长、语气更积极的对抗性言论，往往与更高的有效性评分和仇恨感知度相关。既往使用经验及对ChatGPT等AI写作辅助工具的开放态度，与撰写网络对抗性言论的感知难度呈负相关。总体而言，本研究揭示了社交媒体上对抗性言论形成的语言及身份相关因素，为开发支持性技术和制定内容审核策略以促进有效应对网络仇恨提供了参考依据。