A Knowledge Graph Perspective: Visualization Analysis of Basketball Teaching Research in China
DOI:
https://doi.org/10.52731/lir.v003.111Keywords:
ReferencesReferences, Cite Space, visualization analysisAbstract
China basketball teaching research has gone through a complicated and long road. After more than 60 years' development, great changes have taken place in the research of basketball teaching in many aspects such as curriculum and teaching methods. Scientific knowledge graph is an application software tool which can objectively reflect the research trends of a certain discipline or research field and present a large amount of knowledge information in the form of a specific graph. It can easily make up for the shortcomings of previous research, so as to obtain more rational and scientific research results. In this paper, 5703 kinds of academic journals were collected from the general online database of China Academic Journals in China Knowledge Network, and the database with accurate sample data was arranged. Use the Cite space on the periodical data during the period of 2005-2018 to implement the knowledge map of keyword networks. The time slice of the period 2005-2018 was set to 5, the Top N was set to 50, and the node type was selected as Keywords. Other parameters are set as default parameters. After running the software, we get a co-occurrence knowledge map of keywords. Then we used literature, visualization analysis and other research methods, and applied Cite Space software to analyze the data of the journals selected in this paper, visualize the development history of basketball research in China and the cooperation between institutions and authors, and draw a knowledge graph of the relevant research areas to provide some reference for the development of basketball teaching research in China.
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