Derivation of Key Attributes and Clusters of Korean Taekwondo Policies and Systems on Social Media: Comparative Big Data Analysis Based on Regime Change

This study analyzed the key attributes and clusters of policies and systems of Korean Taekwondo based on Park Geun-Hye and Moon Jae-in’s regime changes using big data, including 8,030 data points on social media over a period of 8 years. Frequency analysis, term frequency inverse document frequency analysis, and degree centrality analysis were performed using TEXTOM 4.5. In addition, a convergent and correlation analysis was performed using UCINET 6 to visualize related words and analyze clusters. Frequency, term frequency inverse document frequency, and degree centrality analyses revealed 30 high-order terms. A convergence of iterated correlations analysis of the derived words identified three common clusters: improvement, problem, and support. In addition, there were two distinct clusters in the Park Geun-hye government (research and sports policy), and three in the Moon Jae-in government (interview, thoughts, and athlete). The Korean government attempted to improve and address problems related to policies and systems for the development of Taekwondo. However, as Taekwondo policies and systems were implemented from different perspectives by each regime, systematic policies and systems could not be implemented.