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Multilingual Hate Speech Detection and Counterspeech Generation: A Comprehensive Survey and Practical Guide

arXiv:2603.19279v1 Announce Type: new Abstract: Combating online hate speech in multilingual settings requires approaches that go beyond English-centric models and capture the cultural and linguistic diversity of global online discourse. This paper presents a comprehensive survey and practical guide to multilingual hate speech detection and counterspeech generation, integrating recent advances in natural language processing. We analyze why monolingual systems often fail in non-English and code-mixed contexts, missing implicit hate and culturally specific expressions. To address these challenges, we outline a structured three-phase framework - task design, data curation, and evaluation - drawing on state-of-the-art datasets, models, and metrics. The survey consolidates progress in multilingual resources and techniques while highlighting persistent obstacles, including data scarcity in low-resource languages, fairness and bias in system development, and the need for multimodal solutions

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Zahra Safdari Fesaghandis, Suman Kalyan Maity · · 1 min read · 7 views
#cs.CL

arXiv:2603.19279v1 Announce Type: new Abstract: Combating online hate speech in multilingual settings requires approaches that go beyond English-centric models and capture the cultural and linguistic diversity of global online discourse. This paper presents a comprehensive survey and practical guide to multilingual hate speech detection and counterspeech generation, integrating recent advances in natural language processing. We analyze why monolingual systems often fail in non-English and code-mixed contexts, missing implicit hate and culturally specific expressions. To address these challenges, we outline a structured three-phase framework - task design, data curation, and evaluation - drawing on state-of-the-art datasets, models, and metrics. The survey consolidates progress in multilingual resources and techniques while highlighting persistent obstacles, including data scarcity in low-resource languages, fairness and bias in system development, and the need for multimodal solutions. By bridging technical progress with ethical and cultural considerations, we provide researchers, practitioners, and policymakers with scalable guidelines for building context-aware, inclusive systems. Our roadmap contributes to advancing online safety through fairer, more effective detection and counterspeech generation across diverse linguistic environments.

Executive Summary

This comprehensive survey and practical guide on multilingual hate speech detection and counterspeech generation presents a structured three-phase framework to address the challenges of monolingual systems in non-English and code-mixed contexts. The authors emphasize the need for culturally specific expressions and multimodal solutions, highlighting data scarcity in low-resource languages and fairness and bias in system development. The roadmap provides scalable guidelines for building context-aware, inclusive systems, contributing to advancing online safety through fairer and more effective detection and counterspeech generation. The authors bridge technical progress with ethical and cultural considerations, making it a valuable resource for researchers, practitioners, and policymakers. By consolidating progress in multilingual resources and techniques, the survey highlights persistent obstacles and provides a roadmap for addressing them.

Key Points

  • ▸ Multilingual hate speech detection and counterspeech generation require approaches beyond English-centric models.
  • ▸ Monolingual systems often fail in non-English and code-mixed contexts due to implicit hate and culturally specific expressions.
  • ▸ Data scarcity in low-resource languages, fairness and bias in system development, and the need for multimodal solutions are persistent obstacles.

Merits

Comprehensive Framework

The authors provide a structured three-phase framework for addressing the challenges of multilingual hate speech detection and counterspeech generation.

Multimodal Solutions

The authors emphasize the need for multimodal solutions to address the complexities of multilingual hate speech detection and counterspeech generation.

Scalable Guidelines

The roadmap provides scalable guidelines for building context-aware, inclusive systems, contributing to advancing online safety.

Demerits

Data Scarcity

The authors highlight data scarcity in low-resource languages as a persistent obstacle, which may limit the effectiveness of multilingual hate speech detection and counterspeech generation.

Fairness and Bias

The authors emphasize the need for fairness and bias in system development, but may not provide sufficient guidance on how to achieve this in practice.

Technical Complexity

The technical complexity of implementing the proposed framework and multimodal solutions may be a barrier to adoption for some researchers and practitioners.

Expert Commentary

The authors' comprehensive survey and practical guide on multilingual hate speech detection and counterspeech generation is a significant contribution to the field. The proposed framework and guidelines provide a valuable roadmap for researchers, practitioners, and policymakers. However, the technical complexity of implementing the proposed framework and multimodal solutions may be a barrier to adoption for some. Additionally, the authors' emphasis on data scarcity in low-resource languages and fairness and bias in system development highlights the need for further research and development in these areas.

Recommendations

  • ✓ Researchers and practitioners should prioritize the development of multimodal solutions and culturally specific expressions to address the complexities of multilingual hate speech detection and counterspeech generation.
  • ✓ Policymakers should allocate resources to address data scarcity in low-resource languages and promote fairness and bias in system development.

Sources

Original: arXiv - cs.CL

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