Modeling Information Popularity Dynamics via Branching Process on Micro-Blog Network

Predicting and modeling of items popularity on web 2.0 have attracted great attention of many scholars. From the perspective of information competition, we propose a probabilistic model using the branching process to characterize the process in which micro-blogging gains its popularity. The model is analytically tractable and can reproduce several characteristics of empirical micro-blogging data on Sina micro-blog, the most popular micro-blogging system in China. We find that the information competition on micro-blog network leads to the decay of information popularity obeying power law distribution with exponent about 1.5, and the value is similar to the exponent of degree distribution of micro-blog network. Furthermore, the mean popularity is decided by the probability of innovating a new message. Our work presents evidence supporting the idea that two distinct factors affect information popularity: information competition and social network structure.