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K-MHaS: A Multi-label Hate Speech Detection Dataset in Korean Online News Comment

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arxiv 2208.10684 v3 pith:NX6AGY5V submitted 2022-08-23 cs.CL cs.AI

K-MHaS: A Multi-label Hate Speech Detection Dataset in Korean Online News Comment

Jean Lee , Taejun Lim , Heejun Lee , Bogeun Jo , Yangsok Kim , Heegeun Yoon , Soyeon Caren Han This is my paper
classification cs.CL cs.AI
keywords hatespeechdatasetdetectionk-mhasmulti-labelonlinehandles
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Online hate speech detection has become an important issue due to the growth of online content, but resources in languages other than English are extremely limited. We introduce K-MHaS, a new multi-label dataset for hate speech detection that effectively handles Korean language patterns. The dataset consists of 109k utterances from news comments and provides a multi-label classification using 1 to 4 labels, and handles subjectivity and intersectionality. We evaluate strong baseline experiments on K-MHaS using Korean-BERT-based language models with six different metrics. KR-BERT with a sub-character tokenizer outperforms others, recognizing decomposed characters in each hate speech class.

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