Research topic analysis of the European Sport Management Quarterly: Topic modeling with Latent Dirichlet Allocation(LDA)

Abstract

Purpose The purpose of this study was to analyze the research topics of the articles which were published through European Sport Management Quarterly(ESMQ) from 2009 to 2018. The prior topic analysis studies of the ESMQ classified topics based on the key words using NASPE-NASSM SMPS categories. Therefore they couldn't fully reflect the content of the articles. Methods The topic modeling of the current study was conducted with the Latent Dirichlet Allocation(LDA) which generates topics based on the word usage in the article. A total of 265 articles were converted from 'pdf' format to 'txt' ANSI format for topic modeling analysis. The whole topic modeling process was done using R program and the model was set to generate 10 topics from the article. Results The 3 sport management experts were hired to label the name of the topics and the name of the topics are as follow : (1) Impact of mega sport event, (2) Cause-related marketing, (3) Factors affecting the results of the competition, (4) Managing sport organization, (5) European sport leagues, (6) Strategic management, (7) Sport economics, (8) Sport in communities, (9) Sport consumers, (10) Elite sports. It is not quite possible to compare the results of the current topic modeling results with the previous ones because of the methodological differences. However, even though the standards are different, Sport marketing topic showed the largest growth among the 10 topics extracted. Conclusions This study used the LDA probabilistic algorithm to analyze research topics, which made the analyses more objective and wholistic. However, the insights of the researchers were still needed to interpret and labeling the topics.