확률형 아이템 뉴스 마이닝

• 영문명: Mining Loot Box News : Analysis of Keyword Similarities Using Word2Vec
• 발행기관: 한국IT서비스학회
• 저자명: 김태경(Taekyung Kim) 손원석(Wonseok Son) 전성민(Seongmin Jeon)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제20권 제2호, 77~90쪽, 전체 14쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2021.04.30

영문 초록

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.

목차

1. 서 론

2. 연구 배경

3. 연구 문제와 연구 방법

4. 데이터 분석 결과

5. 결 론

참고문헌

키워드

Mobile Games Loot-Box Self-Regulation Word2Vec News Big Data Game Industry