When Does Hate Transfer? A Large-Scale Study of Cross-Lingual Hate Speech Detection
cs.CL, cs.AI
Submitted: 2026-10-19
Updated: 2026-10-19
License: http://creativecommons.org/licenses/by/4.0/
The gist: Effective detection of hate content is essential for maintaining healthy online communities, yet performance can vary substantially across languages.
Abstract
Effective detection of hate content is essential for maintaining healthy online communities, yet performance can vary substantially across languages. This work investigates a core practical question: Can training data from one language support hate-speech detection in another language with comparable performance? To answer this question, we conduct a large-scale study across 14 languages. Our analysis includes low-resource languages, offering practical insights into when cross-lingual transfer can support them and where its limitations emerge. These findings inform the design of more reliable multilingual hate-detection systems.
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