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

July 12, 2016 ยท Declared Dead ยท ๐Ÿ› Artificial Intelligence and Interactive Digital Entertainment Conference

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Authors Anders Drachen, Eric Thurston Lundquist, Yungjen Kung, Pranav Simha Rao, Diego Klabjan, Rafet Sifa, Julian Runge arXiv ID 1607.03202 Category stat.ML: Machine Learning (Stat) Cross-listed cs.SI, stat.AP Citations 53 Venue Artificial Intelligence and Interactive Digital Entertainment Conference Last Checked 5 months ago
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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