Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Study on prediction for a film success using text mining

텍스트 마이닝을 활용한 영화흥행 예측 연구

  • Lee, Sanghun (Onsol Communication) ;
  • Cho, Jangsik (Department of Information Statistics, Kyungsung University) ;
  • Kang, Changwan (Department of Data Information Science, Dongeui University) ;
  • Choi, Seungbae (Department of Data Information Science, Dongeui University)
  • 이상훈 ((주) 온솔 커뮤니케이션) ;
  • 조장식 (경성대학교 응용통계학과) ;
  • 강창완 (동의대학교 데이터정보학과) ;
  • 최승배 (동의대학교 데이터정보학과)
  • Received : 2015.07.21
  • Accepted : 2015.09.16
  • Published : 2015.11.30
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Abstract

Recently, big data is positioning as a keyword in the academic circles. And usefulness of big data is carried into government, a local public body and enterprise as well as academic circles. Also they are endeavoring to obtain useful information in big data. This research mainly deals with analyses of box office success or failure of films using text mining. For data, it used a portal site 'D' and film review data, grade point average and the number of screens gained from the Korean Film Commission. The purpose of this paper is to propose a model to predict whether a film is success or not using these data. As a result of analysis, the correct classification rate by the prediction model method proposed in this paper is obtained 95.74%.

최근 빅 데이터는 학계에서 키워드로 자리매김을 하고 있다. 빅 데이터의 유용성은 학계뿐만 아니라 정부, 지자체 그리고 기업체까지 파급되고 있고, 빅 데이터 속에서 유용한 정보를 도출해 내기 위해 노력하고 있다. 본 연구에서는 영화에 대한 리뷰를 가지고 텍스트 마이닝 (text mining)을 이용한 빅 데이터 분석을 수행한다. 본 연구의 목적은 포털 사이트 'D'사와 영화진흥위원회의 영화에 대한 리뷰 데이터, 그리고 고객들의 평점평균 (score)과 스크린 수 (screen number)를 설명변수로 사용하고, 영화 흥행 여부를 종속변수로 하여 로지스틱 회귀분석을 통한 영화 흥행 예측 모형을 제안하는 것이다. 분석결과, 본 연구에서 제안한 예측모형의 정분류율은 95.74%로 얻어졌다.

Keywords

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