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Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games

Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games ADELE LU JIA* , SIQI SHEN, RUUD VAN DE BOVENKAMP, ALEXANDRU IOSUP, FERNANDO KUIPERS, and DICK H. J. EPEMA, Delft University of Technology Multiplayer Online Games (MOGs) like Defense of the Ancients and StarCraft II have attracted hundreds of millions of users who communicate, interact, and socialize with each other through gaming. In MOGs, rich social relationships emerge and can be used to improve gaming services such as match recommendation and game population retention, which are important for the user experience and the commercial value of the companies who run these MOGs. In this work, we focus on understanding social relationships in MOGs. We propose a graph model that is able to capture social relationships of a variety of types and strengths. We apply our model to real-world data collected from three MOGs that contain in total over ten years of behavioral history for millions of players and matches. We compare social relationships in MOGs across different game genres and with regular online social networks like Facebook. Taking match recommendation as an example application of our model, we propose SAMRA, a Socially Aware Match Recommendation Algorithm that takes http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Knowledge Discovery from Data (TKDD) Association for Computing Machinery

Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2015 by ACM Inc.
ISSN
1556-4681
DOI
10.1145/2736698
Publisher site
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Abstract

Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games ADELE LU JIA* , SIQI SHEN, RUUD VAN DE BOVENKAMP, ALEXANDRU IOSUP, FERNANDO KUIPERS, and DICK H. J. EPEMA, Delft University of Technology Multiplayer Online Games (MOGs) like Defense of the Ancients and StarCraft II have attracted hundreds of millions of users who communicate, interact, and socialize with each other through gaming. In MOGs, rich social relationships emerge and can be used to improve gaming services such as match recommendation and game population retention, which are important for the user experience and the commercial value of the companies who run these MOGs. In this work, we focus on understanding social relationships in MOGs. We propose a graph model that is able to capture social relationships of a variety of types and strengths. We apply our model to real-world data collected from three MOGs that contain in total over ten years of behavioral history for millions of players and matches. We compare social relationships in MOGs across different game genres and with regular online social networks like Facebook. Taking match recommendation as an example application of our model, we propose SAMRA, a Socially Aware Match Recommendation Algorithm that takes

Journal

ACM Transactions on Knowledge Discovery from Data (TKDD) – Association for Computing Machinery

Published: Oct 26, 2015

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