Estimating user influence in online social networks subject to information overload

摘要: Online social networks have attracted remarkable attention since they provide various approaches for hundreds of millions people to stay connected with their friends. Due the existence information overload, research on diffusion dynamics in epidemiology cannot be adopted directly that online networks. In this paper, we consider subject and model information-processing process a user by queue batch arrival finite buffer. We use average number times message is processed after it generated given characterize influence, which then estimated through theoretical analysis network. validate accuracy our estimation simulations, apply results study impacts different factors influence. Among observations, find impact network size influence marginal while decreases assortativity due particularly interesting.