Counterspeakers' Perspectives: Unveiling Barriers and AI Needs in the Fight against Online Hate
Jimin Mun, Cathy Buerger, Jenny T. Liang, Joshua Garland, Maarten Sap
摘要
Counterspeech, i.e., direct responses against hate speech, has become an important tool to address the increasing amount of hate online while avoiding censorship. Although AI has been proposed to help scale up counterspeech efforts, this raises questions of how exactly AI could assist in this process, since counterspeech is a deeply empathetic and agentic process for those involved. In this work, we aim to answer this question, by conducting in-depth interviews with 10 extensively experienced counterspeakers and a large scale public survey with 342 everyday social media users. In participant responses, we identified four main types of barriers and AI needs related to resources, training, impact, and personal harms. However, our results also revealed overarching concerns of authenticity, agency, and functionality in using AI tools for counterspeech. To conclude, we discuss considerations for designing AI assistants that lower counterspeaking barriers without jeopardizing its meaning and purpose.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper10
- Lost in Moderation: How Commercial Content Moderation APIs Over- and Under-Moderate Group-Targeted Hate Speech and Linguistic VariationsDavid Hartmann, Amin Oueslati, Dimitri Staufer, Lena Pohlmann 等CHI 2025 · 被引用 37 次
- Outcome-Constrained Large Language Models for Countering Hate SpeechLingzi Hong, Pengcheng Luo, Eduardo Blanco, Xiaoying SongEMNLP 2024 · 被引用 5 次
- Perceiving and Countering Hate: The Role of Identity in Online ResponsesKaike Ping, James Hawdon, Eugenia Ha Rim RhoCSCW 2025 · 被引用 5 次
- A Matter of Perspective(s): Contrasting Human and LLM Argumentation in Subjective Decision-Making on Subtle SexismPaula Akemi Aoyagui, Kelsey Stemmler, Sharon A. Ferguson, Young-Ho Kim 等CHI 2025 · 被引用 4 次
- HateBuffer: Safeguarding Content Moderators' Mental Well-Being through Hate Speech Content ModificationSubin Park, Jeonghyun Kim, Jeanne Choi, Joseph Seering 等CSCW 2025 · 被引用 4 次
它引用的顶会 Paper23
- What is AI Literacy? Competencies and Design ConsiderationsDuri Long, Brian MagerkoCHI 2020 · 被引用 2,947 次
- To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-makingZana Buçinca, Maja Barbara Malaya, Krzysztof Z. GajosCSCW 2021 · 被引用 962 次
- Scalable and Generalizable Social Bot Detection through Data SelectionKai-Cheng Yang, Onur Varol, Pik-Mai Hui, Filippo MenczerAAAI 2020 · 被引用 385 次
- Explanations Can Reduce Overreliance on AI Systems During Decision-MakingHelena Vasconcelos, Matthew Jörke, Madeleine Grunde-McLaughlin, Tobias Gerstenberg 等CSCW 2023 · 被引用 362 次
- Co-Writing with Opinionated Language Models Affects Users' ViewsMaurice Jakesch, Advait Bhat, Daniel Buschek, Lior Zalmanson 等CHI 2023 · 被引用 249 次
相关 Paper
- Empowering Creators in the Fight Against Online Hate: A Qualitative Exploration of AI-Mediated Counterspeech ToolsPhoebe Yiqing Huang, Jiaming Deng, Yingchen Yang, Spencer WilliamsCSCW 2025 · 被引用 2 次
- "Ignorance is not Bliss": Designing Personalized Moderation to Address Ableist Hate on Social MediaSharon Heung, Lucy Jiang, Shiri Azenkot, Aditya VashisthaCHI 2025 · 被引用 14 次
- Echoes of Norms: Investigating Counterspeech Bots' Influence on Bystanders in Online CommunitiesMengyao Wang, Shuai Ma, Nuo Li, Peng Zhang 等CHI 2026 · 被引用 1 次
- Fact-based Counter Narrative Generation to Combat Hate SpeechBrian Wilk, Homaira Huda Shomee, Suman Kalyan Maity, Sourav MedyaWWW 2025 · 被引用 6 次
- Is Safer Better? The Impact of Guardrails on the Argumentative Strength of LLMs in Hate Speech CounteringHelena Bonaldi, Greta Damo, Nicolás Benjamín Ocampo, Elena Cabrio 等EMNLP 2024 · 被引用 2 次
