Analysis of dance philosophy research trends before and after COVID-19 using text mining-based topic modeling

Abstract

The purpose of this study is to identify academic research trends in the field of dance philosophy in Korea before and after COVID-19. For the analysis, keyword analysis and TF-IDF analysis were conducted using text mining and topic modeling analysis techniques using Textome 5.0. In addition, the LDA model was applied to derive the coherence score, then the appropriate number of topics was specified, and visualized using pyLDAvis. As a result of the analysis, first, the top 10 major keywords in the before COVID-19 period were extracted as human, body, ideology, value, dance education, movement, expression, life, Korean dance, and diversity, and in the after COVID-19 period, dance, movement, It was extracted into the following categories: body, dance education, humans, technology, life, artificial intelligence, diversity, and ideology. Second, as a result of TF-IDF analysis in the before COVID-19 period, Korean dance, ideology, Korean dance, Dangun myth, body, dance education, choreographer, movement, human, and Heidegger were extracted as major keywords, and in the after COVID-19 period, artificial intelligence, dance, movement, body, dance education, science and technology, life, Seonyoung Kang, humans, and play were extracted. Third, the dance philosophy research topics in the before COVID-19 period were derived as ‘philosophical meaning of dance education’ and ‘diversity of movement education’. On the other hand, the topics of the after COVID-19 period were derived as ‘the untact era and the direction of dance education’ and ‘the philosophical meaning of dance from the perspective of dance anthropology’.