Bridging Policies, Platforms and Research: Advancing NLP for Hate Speech Proactive Mitigation

ACL ARR 2025 February Submission6897 Authors

Abstract: Despite regulations imposed by nations and social media platforms (Government of India, 2021; European Parliament and Council of the European Union, 2022), hateful content persists as a significant challenge. Existing ap proaches primarily rely on reactive measures such as blocking or suspending offensive messages, with emerging strategies focusing on proactive measurements like detoxification and counterspeech. In this work, we conduct a comprehensive examination of hate speech regulations and strategies from multiple 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.

Paper Type: Long

Research Area: Computational Social Science and Cultural Analytics

Research Area Keywords: hate-speech detection, quantitative analyses of news and/or social media;

Contribution Types: Data analysis, Surveys

Languages Studied: English

Submission Number: 6897