A Visualization Study of Dance Teaching in China Based on the LDA Model and CSSCI Database (1998-2020)

Abstract

Objective: Based on the topics of abstracts, times cited, and co-citation networks, this paper explores the knowledge system of dance teaching in China so as to provide a reference for future research based on bibliometrics. Method: According to the CSSCI database, a statistical analysis of Chinese research in dance teaching from 1998 to 2020 is carried out to discover implicit topics. In view of research hotspots and frontiers, this paper conducts a centrality and visualization analysis and a filtering of salient terms of research hotspots in dance teaching using CiteSpace, a knowledge graph visualization software. Also, the Latent Dirichlet Allocation model is used to extract and visualize the topics from the filtered salient terms of the abstracts. Results/Conclusion: We found that the research hotspots in dance teaching in China can be divided into 16 clusters, namely “Sports Dance”, “Dance Art”, “Classical Chinese Dance”, “Yunnan Dance”, “Dance”, “Folk Dance”, “Ethnic Dance”. “Dance teaching”, “Quality Education”, “College Students”, “Ethnic Minorities”. “Latin Dance”, “Traditional Athletic Maintenance”, “Chorus”, “Fitness Value”, and “Physical Fitness”. The research frontiers in dance teaching lie in the teaching, discovery, protection, restoration, and discipline construction of folk dance and intangible cultural heritage dance genres.