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

2016/07/12 by Drachen, Anders, Lundquist, Eric Thurston, Kung, Yungjen +4
#Applications (stat.AP) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Social and Information Networks (cs.SI)

paper · doi:10.48550/arxiv.1607.03202

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.

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