We investigate the impact of community structure on information spreading with the linear threshold model. Contrary to the common belief that communities hinder information diffusion, we show that strong communities can facilitate global cascades by enhancing local, intra-community spreading. Using both analytical approaches and numerical simulations, we demonstrate the existence of optimal clustering, where global cascades require the minimal number of early adopters.
Azadeh Nematzadeh, Emilio Ferrara, Alessandro Flammini, Yong-Yeol Ahn
"Optimal network clustering for information diffusion"