Journal of Digital Contents Society (디지털콘텐츠학회 논문지)

Digital Contents Society (한국디지털콘텐츠학회)
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A Study on the Prediction Index for Chart Success of Digital Music Contents based on Analysis of Social Data

소셜 데이터 분석을 통한 음원 흥행 예측 지표 연구

  • Kim, Ga-Yeon (Department of Content Convergence, Ewha Womans University) ;
  • Kim, Myoung-Jun (Department of Content Convergence, Ewha Womans University)
  • 김가연 (이화여자대학교 융합콘텐츠학과) ;
  • 김명준 (이화여자대학교 융합콘텐츠학과)
  • Received : 2018.05.25
  • Accepted : 2018.06.25
  • Published : 2018.06.30
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Abstract

The growth rate of the domestic digital music contents market has been remarkable recently. Accordingly, the necessity of prediction for chart success of digital music contents has grown. This paper proposes prediction indexes for chart success of digital music contents through analysis of correlation between social data such as Internet news, SNS and entry rankings in Melon's weekly music charts. We collected a total of 10 social data items for each male and female artist, and executed cluster analysis. Through this, we found meaningful prediction indexes for chart success of digital music contents for each male and female artist.

최근 국내 음원 시장의 성장 속도가 두드러짐에 따라 음원 흥행 예측의 필요성이 커졌다. 본 논문에서는 인터넷 기사, SNS 등 소셜 데이터와 멜론 주간차트 진입 순위의 상관관계를 분석하여 음원 흥행의 예측 지표를 제안한다. 남자 가수와 여자 가수 각각에 대하여 총 10가지 항목의 소셜 데이터를 수집하였고, 군집 분석을 실시하였다. 이를 통해 남자 가수와 여자 가수 각각의 유의미한 음원 흥행 예측 지표를 발견하였다.

Keywords

Acknowledgement

Supported by : 한국연구재단

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