Predicting Virtual World User Population Fluctuations with Deep Learning.
Where this comes from
- Record sourced from PubMed, PMID 27936009.
- Also identified by DOI 10.1371/journal.pone.0167153 and PMC identifier 5147861.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.
Medical subject headings
- Computer-Assisted Instruction
- Internet
- Learning
- User-Computer Interface