확률형 아이템 뉴스 마이닝 : Word2Vec 활용한 키워드 유사도 분석Mining Loot Box News : Analysis of Keyword Similarities Using Word2Vec
- Other Titles
- Mining Loot Box News : Analysis of Keyword Similarities Using Word2Vec
- Authors
- 김태경; 손원석; 전성민
- Issue Date
- Apr-2021
- Publisher
- 한국IT서비스학회
- Keywords
- Mobile Games; Loot-Box; Self-Regulation; Word2Vec; News Big Data; Game Industry
- Citation
- 한국IT서비스학회지, v.20, no.2, pp.77 - 90
- Journal Title
- 한국IT서비스학회지
- Volume
- 20
- Number
- 2
- Start Page
- 77
- End Page
- 90
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/80960
- DOI
- 10.9716/KITS.2021.20.2.077
- ISSN
- 1975-4256
- Abstract
- Online and mobile games represent digital entertainment. Not only the game grows fast, but also it has been noted for unique business models such as a subscription revenue model and free-to-play with partial payment. But, a recent revenue mechanism, called a loot-box system, has been criticized due to overspending, weak protection to teenagers, and more over gambling-like features. Policy makers and research communities have counted on expert opinions, review boards, and temporal survey studies to build countermeasures to minimize negative effects of online and mobile games. In this process, speed was not seriously considered. In this study, we attempt to use a big data source to find a way of observing a trend for policy makers and researchers. Specifically, we tried to apply the Word2Vec data mining algorithm to news repositories. From the findings, we acknowledged that the suggested design would be effective in lightening issues timely and precisely. This study contributes to digital entertainment service communities by providing a practical method to follow up trends; thus, helping practitioners have concrete grounds for balancing public concerns and business purposes.
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Collections - 경영대학 > 경영학부(글로벌경영학) > 1. Journal Articles
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