title: Predicting Virtual World User Population Fluctuations with Deep Learning.
abstract: 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.
authors.affiliation: Interdisciplinary Program in Visual Information Processing, Korea University, Seoul, Korea.
authors.forename: Young Bin
authors.identifier: http://orcid.org/0000-0002-2114-0120
authors.initials: YB
authors.lastname: Kim
authors.affiliation: Department of Computer and Radio Communications Engineering, Korea University, Seoul, Korea.
authors.forename: Nuri
authors.initials: N
authors.lastname: Park
authors.affiliation: Interdisciplinary Program in Visual Information Processing, Korea University, Seoul, Korea.
authors.forename: Qimeng
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: School of Games, Hongik University, Seoul, Korea.
authors.forename: Jun Gi
authors.initials: JG
authors.lastname: Kim
authors.affiliation: School of Games, Hongik University, Seoul, Korea.
authors.forename: Shin Jin
authors.initials: SJ
authors.lastname: Kang
authors.affiliation: Department of Computer and Radio Communications Engineering, Korea University, Seoul, Korea.
authors.forename: Chang Hun
authors.initials: CH
authors.lastname: Kim
mesh_terms: D001185:Artificial Intelligence; D003195:Computer Communication Networks; D003194:Computer-Assisted Instruction / Q000379:methods* / Q000706:statistics & numerical data; D057225:Data Mining / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D020407:Internet; D007858:Learning; D014584:User-Computer Interface