@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://aclanthology.org/2025.findings-acl.824/",
doi = "10.18653/v1/2025.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."
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%0 Conference Proceedings
%T HatePRISM: Policies, Platforms, and Research Integration. Advancing NLP for Hate Speech Proactive Mitigation
%A Rizwan, Naquee
%A Yimam, Seid Muhie
%A Dementieva, Daryna
%A Skupin, Dr. Florian
%A Fischer, Tim
%A Moskovskiy, Daniil
%A Borkar, Aarushi Ajay
%A Geislinger, Robert
%A Saha, Punyajoy
%A Roy, Sarthak
%A Semmann, Martin
%A Panchenko, Alexander
%A Biemann, Chris
%A Mukherjee, Animesh
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Findings of the Association for Computational Linguistics: ACL 2025
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-256-5
%F rizwan-etal-2025-hateprism
%X 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.
%R 10.18653/v1/2025.findings-acl.824
%U https://aclanthology.org/2025.findings-acl.824/
%U https://doi.org/10.18653/v1/2025.findings-acl.824
%P 16008-16022
Markdown (Informal)
[HatePRISM: Policies, Platforms, and Research Integration. Advancing NLP for Hate Speech Proactive Mitigation](https://aclanthology.org/2025.findings-acl.824/) (Rizwan et al., Findings 2025)
ACL
- Naquee Rizwan, Seid Muhie Yimam, Daryna Dementieva, Dr. Florian Skupin, Tim Fischer, Daniil Moskovskiy, Aarushi Ajay Borkar, Robert Geislinger, Punyajoy Saha, Sarthak Roy, Martin Semmann, Alexander Panchenko, Chris Biemann, and Animesh Mukherjee. 2025. HatePRISM: Policies, Platforms, and Research Integration. Advancing NLP for Hate Speech Proactive Mitigation. In Findings of the Association for Computational Linguistics: ACL 2025, pages 16008–16022, Vienna, Austria. Association for Computational Linguistics.