Publication: Predicting Player Type in Social Network Games

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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Participants

Dereck Toker Ben Steichen
Max Birk
University of Saskatchewan

Citation

Toker, D., Steichen, B., Birk, M. 2014. Predicting Player Type in Social Network Games. In User Modeling and User-Adapted Interaction (UMAP 2014), Aalburg, Denmark. 11., Poster.

BibTeX

@inproceedings {365-umap2014_poster_10,
author= {Dereck Toker and Ben Steichen and Max Birk},
title= {Predicting Player Type in Social Network Games},
booktitle= {User Modeling and User-Adapted Interaction (UMAP 2014), Aalburg, Denmark. 11.},
year= {2014},
note= {Poster}
}