CSI: Charged System Influence Model for Human Behavior Prediction

Social influence has been widely studied in areas of viral marketing, information diffusion and health care. Currently, most influence models only deal with a single influence without the interference of other influences. Also, the influence spreading in previous models must be triggered by individuals who have been activated by the influence. In this paper, we argue that it is the attraction from a specific influence makes an individual choose to spread it among multiple influences. Inspired by charged system theory in physics, a new influence model is proposed, considering individual features and social structure features. It also gives a natural description about how individuals make decisions among multiple influences. Then a novel algorithm based on this model is provided to predict human behavior. Extensive experiments on three real-world datasets demonstrate that our model and algorithm statistically outperform the state-of-the-art methods in terms of prediction accuracy.