Rapid Prediction of Player Retention in Free-to-Play Mobile Games
July 12, 2016 ยท Declared Dead ยท ๐ 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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