Predicting player churn in Destiny

a hidden Markov models approach to predicting player departure in a major online game

Marco Tamassia, William Raffe, Rafet Sifa, Anders Drachen, Fabio Zambetta, Michael Hitchens

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

18 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2016 IEEE Conference on Computational Intelligence and Games (CIG)
Subtitle of host publicationproceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-8
Number of pages8
ISBN (Electronic)9781509018833, 9781509018826
ISBN (Print)9781509018840
DOIs
Publication statusPublished - 2016
Event2016 IEEE Conference on Computational Intelligence and Games, CIG 2016 - Santorini, Greece
Duration: 20 Sep 201623 Sep 2016

Other

Other2016 IEEE Conference on Computational Intelligence and Games, CIG 2016
CountryGreece
CitySantorini
Period20/09/1623/09/16

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