European Sport Management Quarterly의 연구 주제 분석: Latent Dirichlet Allocation을 사용한 Topic Modeling = Research topic analysis of the European Sport Management Quarterly: Topic modeling with Latent Dirichlet Allocation(LDA)

다국어 초록 (Multilingual 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.

국문 초록 (Abstract)

[목적] 본 연구는 2009년부터 2018년까지 European Sport Management Quarterly(ESMQ)에서 발간된 논문들의 주제를 분석하는데 목적이 있다. ESMQ에 대한 주제분석이 전무했던 것은 아니지만 실제 어떠한 연구가 이루어지고 있는지에 대한 분석이라기보다는 NASPE-NASSM SMPS를 바탕으로 설정한 주제에 각 논문들을 할당하는 방식으로 주제분석이 이루어졌다. [방법] 본 연구에서는 단어들이 어떤 단어들과 함께 사용되고 있는가를 바탕으로 주제를 추출하는 Latent Dirichlet Allocation(LDA)기반의 토픽모델링(topic modeling)을 이용하여 분석하였다. 이를 위해 PDF파일로 확보한 265개의 논문을 ANSI 형식의 Text File로 변환 시켰으며 분석은 R 프로그램의 스크립트를 이용하였고 topic 수는 10개로 설정하였다. [결과] 10개로 분류된 논문들을 Gamma 수치가 높은 순으로 재정렬하여 각각의 주제를 명명하는데 기준을 삼았는데 각각의 주제는 (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 sports로 명명되었다. 선행연구의 분류기준과 본 연구의 분류기준이 다르기 때문에 두 개의 연구를 직접적으로 비교하는 것은 불가능하다. 하지만 분류기준이 다름에도 불구하고 Sport marketing 주제 영역은 여타의 주제들에 비해 가장 큰 양적 성장이 있던 연구주제인 것으로 나타났다. [결론] 객관적이고 명확한 주제분석을 위하여 LDA 확률모델 알고리즘의 토픽모델링 기법이 적용되었으나 연구자의 통찰력은 여전히 필요하였다. 이에 향후 연구에서는 다양한 토픽 수로 분석하여 비교하거나 데이터의 전처리 여부에 따른 주제 추출 결과 비교를 통해 주제분석의 객관성 확보에 근거가 되기를 기대한다.

참고문헌 (Reference)

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