Statistical mechanics of rumour spreading in network communities

We report a preliminary investigation on interactions between networked social communities using the Ising model to analyze the spread of rumours. The inner opinion of a given community is forced to change through the introduction of a unique external source and we analyze how the other communities react to this change. We model two conceptual external sources: namely, “Strong-belief ”, and “Propaganda”, by an infinitely strong inhomogeneous external field and a finite uniform external field, respectively. In the former case, the community changes independently from other communities while in the latter case according also to interactions with the other communities. We apply our model to synthetic networks as well as various real world data ranging from human physical contact networks to online social networks. The experimental results using real world data clearly demonstrate two distinct scenarios of phase transitions.