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This study examines patterns of online racialized hate speech in South Korea amid rapid demographic change and a strong ethnonationalist identity. Drawing on racial threat theory, we analyze 3,077 racially/ethnically offensive comments from NAVER and YouTube (2020–2022) using the Korean Offensive Language Dataset (KOLD). Using morphological analysis and keyword-frequency categorization, we identify dominant themes and targets. The results show two patterns: hate toward Chinese, Korean-Chinese and Southeast Asians reflects perceived economic, political and cultural threats and is expressed through nationalistic “us vs. them” rhetoric; these groups are the most frequent targets. By contrast, hate targeting Black, Indian and white individuals is less tied to local threat and more to imported global stereotypes about crime, hygiene or racism, reproducing global racial hierarchies. Overall, racialized hate speech in Korea varies by the target group, suggesting the need for tailored policy responses.
Noh et al. (Fri,) studied this question.