Rapid Prediction of Player Retention in Free-to-Play Mobile Games

Anders Drachen, Eric Thurston Lundquist, Yungjen Kung, Pranav Rao, Rafet Sifa, Julian Runge, Diego Klabjan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Predicting and improving player retention is crucial to the success of mobile Free-to-Play games. This paper explores the problem of rapid retention prediction in this context. Heuristic modeling approaches are introduced as a way of building simple rules for predicting short-term retention. Compared to common classification algorithms, our heuristic-based approach achieves reasonable and comparable performance using information from the first session, day, and week of player activity.
Original languageEnglish (US)
Title of host publicationTwelfth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE-16)
Pages23-29
Number of pages7
StatePublished - 2016

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    Drachen, A., Lundquist, E. T., Kung, Y., Rao, P., Sifa, R., Runge, J., & Klabjan, D. (2016). Rapid Prediction of Player Retention in Free-to-Play Mobile Games. In Twelfth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE-16) (pp. 23-29)