@inproceedings{rizwan-etal-2025-hateprism,
    title = "{H}ate{PRISM}: Policies, Platforms, and Research Integration. Advancing {NLP} for Hate Speech Proactive Mitigation",
    author = "Rizwan, Naquee  and
      Yimam, Seid Muhie  and
      Dementieva, Daryna  and
      Skupin, Dr. Florian  and
      Fischer, Tim  and
      Moskovskiy, Daniil  and
      Borkar, Aarushi Ajay  and
      Geislinger, Robert  and
      Saha, Punyajoy  and
      Roy, Sarthak  and
      Semmann, Martin  and
      Panchenko, Alexander  and
      Biemann, Chris  and
      Mukherjee, Animesh",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.findings-acl.824/",
    pages = "16008--16022",
    ISBN = "979-8-89176-256-5",
    abstract = "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."
}