Predicting Player Type in Social Network Games

نویسندگان

  • Dereck Toker
  • Ben Steichen
  • Max Birk
چکیده

This paper presents preliminary work towards personalizing and recommending social network games based on a user’s player type. In particular, we present research aimed at supporting such personalization through the prediction of player type from automatically collected user data. We first provide a brief overview of player types, and then outline several data sources that we gathered from a popular social network game to study the feasibility of player type predictions. Finally, we perform a preliminary analysis using one of these sources, namely music interests.

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تاریخ انتشار 2014