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텍스트마이닝 기법을 활용한 게임 스트리밍 애플리케이션 리뷰 분석: 디지털 경쟁력 강화를 위한 연구

Analyzing Game Streaming Application Reviews Using Text Mining Approach: Research to Strengthen Digital Competitiveness

  • ;
  • 이정우 (연세대학교 정보대학원)
  • Jin, Wenhui (Department of Management of Technology, Yonsei University) ;
  • Lee, Jungwoo (Graduate School of Information, Yonsei University)
  • 투고 : 2022.02.17
  • 심사 : 2022.04.20
  • 발행 : 2022.04.28

초록

코로나 19로 인해 라이브 스트리밍 서비스 시장의 성장이 가속화되고 있어 라이브 스트리밍 모바일 애플리케이션의 다운로드와 리뷰의 수도 급격히 증가하고 있다. 본 연구에서는 게임 스트리밍 서비스 기업 중 하나인 트위치(Twitch)의 모바일 애플리케이션을 대상으로 하여 텍스트마이닝 기법 중 LDA 토픽모델링을 통해 총 8개의 토픽을 추출하였는데 그중 7가지 불편요인들이 추출되고, 공기어 분석 방법을 활용해 사용자 리뷰를 분석하여 사용자가 주로 느끼는 5가지 불편요인들을 탐지하여, 최종, 광고, UI 디자인, 기술문제를 해결하는 동시에 디지털 경쟁력도 강화할 수 있는 솔루션을 제공하였다. 본 연구에서 제공한 솔루션은 향후 트위치(Twitch)뿐만 아니라 타 라이브 스트리밍 서비스 기업에도 디지털 경쟁력을 향상할 수 있는 기회를 제공할 수 있을 것이다. 향후 본 연구에서 제공한 솔루션의 유용성 및 신뢰성을 판단하기 위해 진일보 연구할 가치가 있다.

As the growth of the live streaming service market is accelerating due to COVID-19, the number of downloads and reviews of live streaming mobile applications is also rapidly skyrocketing. This study is to research game streaming applications using Twitch reviews as database. A total of 8 topics are extracted through LDA topic modeling and 7 out of them are detected to be inconvenience factors. Then, to pinpoint the main inconvenience factors, co-occurrence analysis is used in order to find out main factors. Finally, based on previous studies, several solutions are provided, which can solve the inconvenience factors(advertisement, UI design, technology problems) as well as strengthening digital competitiveness. This study will serve as an opportunity to improve digital competitiveness not only for Twitch but also for other game live streaming service companies in the future.

키워드

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