HatePRISM: Policies, Platforms, and Research Integration. Advancing NLP for Hate Speech Proactive Mitigation
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Abstract (arXiv)
Despite regulations imposed by nations and social media platforms, e.g. (Government of India, 2021; European Parliament and Council of the European Union, 2022), inter alia, hateful content persists as a significant challenge. Existing approaches primarily rely on reactive measures such as blocking or suspending offensive messages, with emerging strategies focusing on proactive measurements like detoxification and counterspeech. In our work, which we call HatePRISM, we conduct a comprehensive examination of hate speech regulations and strategies from three perspectives: country regulations, social platform policies, and NLP research datasets. Our findings reveal significant inconsistencies in hate speech definitions and moderation practices across jurisdictions and platforms, alongside a lack of alignment with research efforts. Based on these insights, we suggest ideas and research direction for further exploration of a unified framework for automated hate speech moderation incorporating diverse strategies.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 30 of its 94 references that are in the map. First posted on arXiv 6 Jul 2025.
Builds on
30 of 94 references.
References · 30
- 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 736
- 2020HateXplain: A Benchmark Dataset for Explainable Hate Speech Detectioncited by 407
- 2018Large Scale Crowdsourcing and Characterization of Twitter Abusive Behaviorcited by 270
- 2020Directions in Abusive Language Training Data: Garbage In, Garbage Outcited by 140
- 2019Multilingual and Multi-Aspect Hate Speech Analysiscited by 133
- 2018Thou shalt not hate: Countering Online Hate Speechcited by 64
- 2018Fighting Offensive Language on Social Media with Unsupervised Text Style Transfercited by 55
- 2019Offensive Language and Hate Speech Detection for Danishcited by 49
- 2021SWSR: A Chinese Dataset and Lexicon for Online Sexism Detectioncited by 42
- 2020Hate Speech detection in the Bengali language: A dataset and its baseline evaluationcited by 37
- 2021Detecting Harmful Content On Online Platforms: What Platforms Need Vs. Where Research Efforts Gocited by 33
- 2020Hostility Detection Dataset in Hindicited by 31
18 more
- 2020Artificial Intelligence for Social Good: A Surveycited by 29
- 2020DeepHateExplainer: Explainable Hate Speech Detection in Under-resourced Bengali Languagecited by 26
- 2024NLP for Counterspeech against Hate: A Survey and How-To Guidecited by 22
- 2022Hate Speech and Offensive Language Detection in Bengalicited by 19
- 2021How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impactcited by 18
- 2020Towards A Friendly Online Community: An Unsupervised Style Transfer Framework for Profanity Redactioncited by 17
- 2023Understanding Counterspeech for Online Harm Mitigationcited by 17
- 2024On Zero-Shot Counterspeech Generation by LLMscited by 17
- 2024Counterspeakers' Perspectives: Unveiling Barriers and AI Needs in the Fight against Online Hatecited by 15
- 2021Methods for Detoxification of Texts for the Russian Languagecited by 13
- 2021Empowering NGOs in Countering Online Hate Messagescited by 13
- 2024Multilingual and Explainable Text Detoxification with Parallel Corporacited by 12
- 2024"Community Guidelines Make this the Best Party on the Internet": An In-Depth Study of Online Platforms' Content Moderation Policiescited by 11
- 2020Reducing Unintended Identity Bias in Russian Hate Speech Detectioncited by 10
- 2023The DSA Transparency Database: Auditing Self-reported Moderation Actions by Social Mediacited by 10
- 2022Counter Hate Speech in Social Media: A Surveycited by 5
- 2022CoRAL: a Context-aware Croatian Abusive Language Datasetcited by 4
- 2024Exploring Boundaries and Intensities in Offensive and Hate Speech: Unveiling the Complex Spectrum of Social Media Discoursecited by 4
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Citing papers per year: 2026: 1.
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