Text Mining-Based Analysis of Social Perception and Semantic Structure of Online Discourse Related to Gateball and the Elderly

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This research aims to analyze the social perception and semantic structure of online discourse related to gateball and the elderly using text mining techniques.
Collected online text data from major portal sites (Naver, Daum, Google) from 2015 to 2024.
Conducted analyses including word frequency analysis, TF-IDF analysis, sentiment analysis, semantic network analysis, and CONCOR analysis.
Identified key themes and emotional sentiments related to gateball and elderly welfare.
Keyword analysis revealed 'elderly', 'gateball', 'center', and 'elderly welfare' as prominent terms, indicating gateball's recognition as a significant activity for elderly welfare.
Sentiment analysis showed a higher proportion of neutral sentiment, with positive sentiment surpassing negative sentiment, suggesting a generally positive image of gateball.
Semantic network analysis highlighted 'elderly' and 'gateball' as central nodes, connecting to 'health', 'participation', and 'lifestyle sports'.

Analyzes social perception of gateball in the elderly, suggesting its health benefits and community impact.

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Jeon et al. (2026) studied this question.

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