Design influence on player retention: A method based on time varying survival analysis
T Allart, G Levieux, M Pierfitte… - … IEEE Conference on …, 2016 - ieeexplore.ieee.org
T Allart, G Levieux, M Pierfitte, A Guilloux, S Natkin
2016 IEEE Conference on Computational Intelligence and Games (CIG), 2016•ieeexplore.ieee.orgThis paper proposes a method to help understanding the influence of a game design on
player retention. Using Far Cry® 4 data, we illustrate how playtime measures can be used to
identify time periods where players are more likely to stop playing. First, we show that a
benchmark can easily be performed for every game available on Steam using publicly
available data. Then, we introduce how survival analysis can help to model the influence of
game variables on player retention. Game environment and player characteristics change …
player retention. Using Far Cry® 4 data, we illustrate how playtime measures can be used to
identify time periods where players are more likely to stop playing. First, we show that a
benchmark can easily be performed for every game available on Steam using publicly
available data. Then, we introduce how survival analysis can help to model the influence of
game variables on player retention. Game environment and player characteristics change …
This paper proposes a method to help understanding the influence of a game design on player retention. Using Far Cry ® 4 data, we illustrate how playtime measures can be used to identify time periods where players are more likely to stop playing. First, we show that a benchmark can easily be performed for every game available on Steam using publicly available data. Then, we introduce how survival analysis can help to model the influence of game variables on player retention. Game environment and player characteristics change over time and tracking systems already store those changes. But existing model which deals with time varying covariate cannot scale on huge datasets produced by video game monitoring. That is why we propose a model that can both deal with time varying covariates and is well suited for big datasets. As a given game variable can have a changing effect over time, we also include time-varying coefficients in our model. We used this survival analysis model to quantify the effect of Far Cry 4 weapons usage on player retention.
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