Optimal network modularity for information diffusion

Azadeh Nematzadeh, Emilio Ferrara, Alessandro Flammini, Yong-Yeol Ahn

We investigate the impact of community structure on information diffusion with the linear threshold model. Our results demonstrate that modular structure may have counter-intuitive effects on information diffusion when social reinforcement is present. We show that strong communities can facilitate global diffusion by enhancing local, intra-community spreading. Using both analytic approaches and numerical simulations, we demonstrate the existence of an optimal network modularity, where global diffusion require the minimal number of early adopters.

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