Modeling and Predicting Popularity Dynamics via Reinforced Poisson Processes

Understand

An ability to predict the popularity dynamics of individual items within a complex evolving system has important implications in an array of areas.

• Here we propose a generative probabilistic framework using a reinforced Poisson process to model explicitly the process through which individual items gain their popularity.
• This model distinguishes itself from existing models via its capability of modeling the arrival process of popularity and its remarkable power at predicting the popularity of individual items.
• It possesses the flexibility of applying Bayesian treatment to further improve the predictive power using a conjugate prior.