Understanding spreading patterns on social networks based on network topology

Ever since the introduction of the first epidemic model, scientists have tried extrapolating the damage caused by a contagious disease, given its spreading pattern in the premature stage. However, understanding epidemiology remains an elusive mystery to researchers specifically because of the unavailability of large amount of data. We utilise the study of diffusion of memes in a social networking website to solve this problem. In this paper, we analyse the impact of specific meso-scale properties of a network on a meme traversing over it. We have employed SCCP (Scale free, Communities, Core Periphery structure) networks for analysis purpose. We propose a new meme propagation model for real world social networks and observe the cause of virality of a meme. We have tested and validated our model with the real world information spreading pattern.