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We suggest a multilabel Korean online hate speech dataset that covers sevencategories of hate speech: (1) Race and Nationality, (2) Religion, (3)Regionalism, (4) Ageism, (5) Misogyny, (6) Sexual Minorities, and (7) Male. Our35K dataset consists of 24K online comments with Krippendorff's Alpha labelaccordance of .713, 2.2K neutral sentences from Wikipedia, 1.7K additionallylabeled sentences generated by the Human-in-the-Loop procedure andrule-generated 7.1K neutral sentences. The base model with 24K initial datasetachieved the accuracy of LRAP .892, but improved to .919 after being combinedwith 11K additional data. Unlike the conventional binary hate and non-hatedichotomy approach, we designed a dataset considering both the cultural andlinguistic context to overcome the limitations of western culture-based Englishtexts. Thus, this paper is not only limited to presenting a local hate speechdataset but extends as a manual for building a more generalized hate speechdataset with diverse cultural backgrounds based on social science perspectives.

Korean Online Hate Speech Dataset for Multilabel Classification: How Can Social Science Improve Dataset on Hate Speech?