Modeling for Information Diffusion in Online Social Networks via Hydrodynamics

Abstract

In recent years, online social networks have gained tremendous popularity because of the massive number of online users, the fast spread of information, and strong inter-personal influence. However, due to the high complexity of the user interaction and the real-time changing of the online social networks, it is still a big challenge to model the spreading process of the information delicately and, then, to predict the information diffusion precisely. In this paper, we exploit a hydrodynamic model to describe the spreading process of the information in online social networks. By using the proposed hydrodynamic information diffusion prediction model (hydro-IDP), we can describe the spreading process of the information on both temporal and spatial perspectives. It is also helpful in extracting the characteristics of information diffusion (e.g., the information popularity, the user influence, and the diffusivity of social platform). We also consider the superimposed effect of the information diffusion resulted from influential users in the model. The high accuracy of the model results has illustrated that our proposed Hydro-IDP model is competent to describe and predict the spreading process of information in online social networks.