TY - JOUR
T1 - Predicting virtual world user population fluctuations with deep learning
AU - Kim, Young Bin
AU - Park, Nuri
AU - Zhang, Qimeng
AU - Kim, Jun Gi
AU - Kang, Shin Jin
AU - Kim, Chang Hun
N1 - Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education, Science, ICT and future Planning (NRF-2014R1A2A2A01007143, NRF- 2015R1A2A1A16074940, and NRF- 2015R1A1A1A05001196) and the ICT R&D program of MSIP/IITP (R-20160404-003511, High performance computing (HPC) based rendering solution development). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
PY - 2016/12
Y1 - 2016/12
N2 - 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.
AB - 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.
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U2 - 10.1371/journal.pone.0167153
DO - 10.1371/journal.pone.0167153
M3 - Article
C2 - 27936009
AN - SCOPUS:85006054913
VL - 11
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 12
M1 - e0167153
ER -