Predicting Virtual World User Population Fluctuations with Deep Learning

  • Kim, Young Bin; 
  • Park, Nuri; 
  • Zhang, Qimeng; 
  • Kim, Jun Gi; 
  • Kang, Shin Jin; 
  • 외 1명
Citations

WEB OF SCIENCE

4
Citations

SCOPUS

5

초록

This paper proposes a system for predicting increases in virtual world user actions. The virtual world user population is a very important aspect of these worlds; however, methods for predicting fluctuations in these populations have not been well documented. Therefore, we attempt to predict changes in virtual world user populations with deep learning, using easily accessible online data, including formal datasets from Google Trends, Wikipedia, and online communities, as well as informal datasets collected from online forums. We use the proposed system to analyze the user population of EVE Online, one of the largest virtual worlds.

키워드

GAME; NETWORKS; FORECASTS; PATTERNS; BEHAVIOR; LIFE
제목
Predicting Virtual World User Population Fluctuations with Deep Learning
저자
Kim, Young Bin; Park, Nuri; Zhang, Qimeng; Kim, Jun Gi; Kang, Shin Jin; Kim, Chang Hun
DOI
10.1371/journal.pone.0167153
발행일
2016-12
유형
Article
저널명
PLoS One
권
11
호
12