Ageism in Korean Online Discourse: A Text-Mining Analysis of 10,000 Comments on Older Adults

Abstract

Population aging has intensified debates about the economic, political, and social roles of older adults in South Korea. This study analyzed 10,000 Korean-language online comments to examine ageism through keyword frequency, TF-IDF, n-gram analysis, LDA topic modeling, sentiment classification, and human-assisted content coding. Policy criticism (21.0%) and behavioral criticism (17.0%) were the most frequent categories, while five potentially stigmatizing categories accounted for 34.0% of comments. The findings highlight the importance of distinguishing age-related prejudice from criticism of specific behaviors or policies and contribute to research on ageism, online discourse, and intergenerational relations.