Hyunju Kim , Heehwa Lee
DOI:10.26584/RDPA.2026.10.1.139 Vol.10(No.1) 139-154, 2026
Abstract
This study explores how social perceptions and practice-related discourses on diet dance are structured and circulated in online spaces. Using Textom 6.0, we collected and refined 2,859 online text documents produced over a three-year period starting in 2023 from major portals and social media (e.g., Naver, Daum, and Google). After removing duplicates and irrelevant or promotional content, the dataset was preprocessed through morphology-based procedures, including stop-word removal, consolidation of synonymous terms, and lexical normalization. We then identified salient keywords using word frequency and TF-IDF metrics, examined keyword relationships via co-occurrence-based semantic network analysis, and derived semantic clusters using CONCOR analysis. The discourse was organized around a core axis of “diet-dance-exercise” while integrating multiple interconnected dimensions, including exercise practices, body management indicators, participation environments, online-mediated practice, emotional and leisure experiences, and program/genre expansion. CONCOR analysis yielded seven semantic clusters, indicating that diet dance is not framed solely as a weight-loss exercise but is constructed as a multifaceted social practice shaped by body-management concerns, participation environments, digitally mediated practices, emotional and leisure experiences, and conditions of accessibility and entry. These findings provide empirical evidence for program development, community sport and health promotion policy design, and future measurement development.
Key Words
Diet Dance, Text Mining, Semantic Network Analysis, CONCOR Analysis, TF-IDF