title: Optimal network modularity for information diffusion.
abstract: We investigate the impact of community structure on information diffusion with the linear threshold model. Our results demonstrate that modular structure may have counterintuitive effects on information diffusion when social reinforcement is present. We show that strong communities can facilitate global diffusion by enhancing local, intracommunity spreading. Using both analytic approaches and numerical simulations, we demonstrate the existence of an optimal network modularity, where global diffusion requires the minimal number of early adopters.
authors.affiliation: School of Informatics and Computing, Indiana University, Bloomington, Indiana 47408, USA.
authors.forename: Azadeh
authors.initials: A
authors.lastname: Nematzadeh
authors.affiliation: School of Informatics and Computing, Indiana University, Bloomington, Indiana 47408, USA.
authors.forename: Emilio
authors.initials: E
authors.lastname: Ferrara
authors.affiliation: School of Informatics and Computing, Indiana University, Bloomington, Indiana 47408, USA.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Flammini
authors.affiliation: School of Informatics and Computing, Indiana University, Bloomington, Indiana 47408, USA.
authors.forename: Yong-Yeol
authors.initials: YY
authors.lastname: Ahn
mesh_terms: D019058:Community Networks; D033181:Information Dissemination; D008962:Models, Theoretical