Behavioral Communities and the Atomic Structure of Networks

Abstract

We develop a method of detecting the 'behavioral communities' of a social network based on how people act when they coordinate with their friends' behaviors. There can be multiple different 'conventions' (equilibria or outcomes of a diffusion) in which people in some parts of the network adopt a behavior while people in other parts of the network do not. We define atoms/communities to be groups of people whose behaviors are closely tied together: they behave the same as each other in every convention. This provides a microfoundation for a method of detecting communities in social and economic networks. We characterize such behavioral communities in some random graphs as a function of the behavior, and provide an algorithm for identifying the toms/communities. We discuss and illustrate applications including: optimally seeding diffusion of behaviors involving peer influence, detecting which demographics or nodal characteristics define a society's communities, estimating the strength of peer influence on behavior, as well as missing network data, by observing conventions.

Keywords: Social Networks, Networks, Cohesion, Community Detection, Communities, Games on Networks, Coordination, Complementarities, Peer Effects, Peer Influence, Diffusion, Contagion, Atoms

JEL Classification: D85, D13, L14, O12, Z13