earticle

영어

The purpose of this study is to empirically analyze the structural patterns and thematic characteristics of social discussions on universal design by applying text mining techniques to domestic news coverage. The dataset consisted of 280 news articles collected from Google News as of October 28, 2025, using Universal Design as the main keyword. After excluding duplicates and irrelevant articles, the final dataset was constructed using the full text of the selected reports. Data processing was conducted in a Python 3.12 environment, employing frequency analysis, word cloud visualization, N-gram extraction, ego-network analysis, and co-occurrence network analysis. The results showed that keywords such as application, public, welfare, city, and safety appeared most frequently, indicating that universal design has been discussed across diverse sectors. Network analysis further revealed that all and application served as central hubs, closely interconnected with terms such as welfare, public, and policy. In addition, the co-occurrence analysis identified three major thematic clusters—lifestyle and welfare, policy and institutional, and spatial and design—demonstrating that universal design spans social, cultural, and industrial domains. Overall, the findings indicate that universal design functions as a broad societal value linked to inclusion and public interest, underscoring the need for wider application across policy, industry, and civic sectors.