A Stochastic Model for Measuring Popularity and Reliability in Social Network Systems

Popularity and reliability information are crucial ingredients of today social networking systems such as Facebook, Linked In, YouTube, Twitter, and so on. In this paper, we propose a stochastic model for measuring and ranking popularity and reliability information in social networks. Specifically, by using the relationships between co-occurring users, we model a Markov chain for reliability measures and a queuing model for popularity measures based on time, space and scenarios. We then form a convex combination or fusion of the two measures to compute the Integrated Global Rank for social networks systems. Finally, we present some illustrative simulation results by using the social networks data collected from Twitter and YouTube. Experimental study indicates the effectiveness of proposed ranking algorithm in terms of better search results.