Can Deep Learning Predict Problematic Gaming?

摘要

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.