한국게임학회 논문지 (Journal of Korea Game Society)

  • 제17권3호
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  • Pages.33-44
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  • 2017
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  • 1598-4540(pISSN)
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  • 2287-8211(eISSN)
한국게임학회 (Korea Game Society)
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게임 유용성 평가에 미치는 요인에 관한 연구: 스팀(STEAM) 게임 리뷰데이터 분석

A Study of Factors Influencing Helpfulness of Game Reviews: Analyzing STEAM Game Review Data

  • 강하나 (한림대학교 인터랙션 디자인 대학원) ;
  • 용혜련 (한림대학교 인터랙션 디자인 대학원) ;
  • 황현석 (한림대학교 경영학부)
  • 투고 : 2017.05.17
  • 심사 : 2017.06.19
  • 발행 : 2017.06.30
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초록

인터넷 환경의 발달로 소비자들 사이에 상품정보에 대한 의견이 교환되기 시작하면서 다양한 형식의 온라인 리뷰들이 급속도로 생성되고 있다. 이러한 추세에 따라, 기업들은 온라인 리뷰들을 분석하여 마케팅, 세일즈, 제품개발 등의 다양한 기업 활동에서 그 결과를 활용하려는 노력을 진행하고 있다. 그러나 대표적인 경험재인 '게임'과 관련된 산업에서의 온라인 리뷰에 대한 연구는 매우 부족한 실정이다. 이에 본 연구는 머신러닝 모델을 활용하여 스팀(STEAM)게임의 커뮤니티 데이터를 분석하였다. 이를 통해 타 사용자의 게임 리뷰를 유용하다고 판단하는데 영향을 미치는 요인을 분석하고, 리뷰의 유용성을 예측하는데 있어 가장 우수한 성능을 보인 모델과 변수들을 도출하여 사용자의 충성도와 사용성을 증대시키기 위한 제안을 하고자 한다.

With the development of the Internet environment, various types of online reviews are being generated and exchanged among consumers to share their opinions. In line with this trend, companies are making efforts to analyze online reviews and use the results in various business activities such as marketing, sales, and product development. However, research on online review in industry related to 'Video Game' which is representative experience goods has not been performed enough. Therefore, this study analyzed STEAM community review data using machine learning techniques. We analyzed the factors affecting the opinion of other users' game review. We also propose managerial implications to incease user loyalty and usability.

키워드

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