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http://dx.doi.org/10.14400/JDC.2022.20.4.279

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

Jin, Wenhui (Department of Management of Technology, Yonsei University)
Lee, Jungwoo (Graduate School of Information, Yonsei University)
Publication Information
Journal of Digital Convergence / v.20, no.4, 2022 , pp. 279-290 More about this Journal
Abstract
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.
Keywords
Game Streaming Application; User Review Analysis; Text Mining; LDA Topic Modeling; Co-occurrence Analysis; Digital Competitiveness;
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