Knowledge Structure and Thematic Evolution Analysis of Korean DanceSport Research : A Text Mining and Semantic Network Analysis Approach (2000–2025)

Objectives This study aims to examine research trends in Korean Dance Sports from 2000 to 2025, focusing on thematic developments and structural changes in response to social and policy shifts. Methods A total of 152 academic papers from the RISS database were analyzed using text mining techniques, including TF-IDF, word frequency analysis, semantic network analysis, and CONCOR clustering. Results Early studies centered on individual-level topics like participation motivation and psychological traits. More recent research has shifted to themes such as educational interventions, elderly health, and psychological well-being, reflecting Korea’s demographic and educational changes. Semantic network analysis supported Lee and Sung’s (2009) hypothesis, revealing a move toward a more integrated research structure. High-centrality keywords such as “elderly,” “education,” and “participation” highlight the field’s growing relevance to societal challenges. Conclusions The findings suggest that Dance Sports research increasingly intersects with public health, education, and aging policy. This study offers a foundation for future interdisciplinary research and evidence-based policy design.