How does one build a healthy gaming ecosystem? Recent evidence clearly demonstrates the existence of problematic gaming [1]. Predicting problematic gaming is still in its infancy. Here we focus on excessive gaming and model in-game behaviour as a means to continuously predict future play time. This can be used to help players maintain a healthy balance between the virtual and real worlds. To do this, we convert game log data into time-series and label such data with criteria of problematic gaming. Deep learning is then used to solve the resulting multi-class classification problem.
Qirui Wu and Jacques Carette. 2020. Can Deep Learning Predict Problematic Gaming?. In Proceedings of the 2020 IEEE Conference on Games (CoG 2020). August 24—27, 2020, Osaka, Japan. IEEE, New York, NY, USA, 662-665. https://doi.org/10.1109/CoG47356.2020.9231887