토픽모델링을 사용한 Journal of Sport Management의 연구 주제 분석

초록

The purpose of the study is to classify the topics of the research published between 2009 and 2018 through the Journal of Sport Management(JSM). Due to the high reputation of JSM in the discipline of sport management, the previous studies also looked into the topics of the studies in JSM. Although previous studies classified the topics using only titles, key words, and/or abstracts, the current study used the whole text of the research using topic modeling of a text mining technique. The current study used the Latent Dirichlet Allocation(LDA) algorithm of the tm package of R program. The PDF files of the 367 studies were downloaded from the electronic database and transformed into a text file of ANSI format. The reference list of each text file was erased manually due to its possible influence on the results. After a total of 10 topics were retrieved, a list of studies was assorted based on their Gamma scores. The assorted list of studies was sent to three-panel experts who had published studies through JSM. A panel of three experts agreed on the naming of topics and the topics are (1) sponsorship and endorsement, (2) studies on sport organizations, (3) diversity management, (4) role conflict, (5) sport event & tourism, (6) professional sports, (7) governance in sport, (8) consumer behavior, (9) studies on sport management and social impact of mega-sport event, (10) sport service and satisfaction. It was found that these 10 classified topics had different structures from the previous studies. It is true that the sub-disciplines of sport management do exist as the previous studies had shown. However it was empirically confirmed though topic modeling that the JSM articles did not reflect some sub-disciplines(e.g., sport finance, organizational behavior, sport law, etc.) as a main area of the sport management studies.

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