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Predicting player churn in destiny. A Hidden Markov models approach to predicting player departure in a major online game

 
: Tamassia, M.; Raffe, W.; Sifa, R.; Drachen, A.; Zambetta, F.; Hitchens, M.

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Institute of Electrical and Electronics Engineers -IEEE-:
IEEE Conference on Computational Intelligence and Games, CIG 2016 : 20-23 Sept. 2016, Santorini
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-5090-1883-3
ISBN: 978-1-5090-1882-6
ISBN: 978-1-5090-1884-0
S.325-332
Conference on Computational Intelligence and Games (CIG) <2016, Santorini>
Englisch
Konferenzbeitrag
Fraunhofer IAIS ()

Abstract
Destiny is, to date, the most expensive digital game ever released with a total operating budget of over half a billion US dollars. It stands as one of the main examples of AAA titles, the term used for the largest and most heavily marketed game productions in the games industry. Destiny is a blend of a shooter game and massively multi-player online game, and has attracted dozens of millions of players. As a persistent game title, predicting retention and churn in Destiny is crucial to the running operations of the game, but prediction has not been attempted for this type of game in the past. In this paper, we present a discussion of the challenge of predicting churn in Destiny, evaluate the area under curve (ROC) of behavioral features, and use Hidden Markov Models to develop a churn prediction model for the game.

: http://publica.fraunhofer.de/dokumente/N-502683.html