Predicting Virtual World User Population Fluctuations with Deep Learning
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| Publicat a: | PLoS One vol. 11, no. 12 (Dec 2016), p. e0167153 |
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| Autor principal: | |
| Altres autors: | , , , , |
| Publicat: |
Public Library of Science
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| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text Full Text - PDF |
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| 022 | |a 1932-6203 | ||
| 024 | 7 | |a 10.1371/journal.pone.0167153 |2 doi | |
| 035 | |a 1847562984 | ||
| 045 | 2 | |b d20161201 |b d20161231 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Young Bin Kim | |
| 245 | 1 | |a Predicting Virtual World User Population Fluctuations with Deep Learning | |
| 260 | |b Public Library of Science |c Dec 2016 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 610 | 4 | |a Korea University Wikipedia Radio Communications | |
| 653 | |a Economic | ||
| 653 | |a Research | ||
| 653 | |a Radio communications | ||
| 653 | |a International conferences | ||
| 653 | |a Population | ||
| 653 | |a Computer & video games | ||
| 653 | |a Internet | ||
| 653 | |a Trends | ||
| 653 | |a Signal processing | ||
| 653 | |a Interdisciplinary aspects | ||
| 653 | |a Researchers | ||
| 653 | |a Virtual communities | ||
| 653 | |a Community | ||
| 653 | |a Fluctuations | ||
| 653 | |a Use statistics | ||
| 653 | |a Populations | ||
| 653 | |a Studies | ||
| 653 | |a Information processing | ||
| 653 | |a Data collection | ||
| 653 | |a Acoustics | ||
| 653 | |a Economic activity | ||
| 653 | |a Deep learning | ||
| 653 | |a Datasets | ||
| 700 | 1 | |a Park, Nuri | |
| 700 | 1 | |a Zhang, Qimeng | |
| 700 | 1 | |a Kim, Jun Gi | |
| 700 | 1 | |a Shin Jin Kang | |
| 700 | 1 | |a Kim, Chang Hun | |
| 773 | 0 | |t PLoS One |g vol. 11, no. 12 (Dec 2016), p. e0167153 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1847562984/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/1847562984/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1847562984/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |