Behavioral Communities and the Atomic Structure of Networks

TL;DR

This paper introduces the concept of behavioral communities as atomic structures within social networks, analyzing how peer effects influence these communities and demonstrating improved diffusion strategies and estimation methods.

Contribution

It defines behavioral communities as network atoms, analyzes their dynamics under peer effects, and shows how to leverage this for better diffusion and peer effect estimation.

Findings

Atoms change with peer effect intensity

Seeding based on atoms improves diffusion

Observed behaviors can estimate peer effects

Abstract

When people prefer to coordinate their behaviors with their friends -- e.g., choosing whether to adopt a new technology, to protest against a government, to attend university -- divisions within a social network can sustain different behaviors in different parts of the network. We define a society's `behavioral communities' via its network's `atoms': groups of people who adopt the same behavior in every equilibrium. We analyze how the atoms change with the intensity of the peer effects, and characterize the atoms in a prominent class of network models. We show that using knowledge of atoms to seed the diffusion of a behavior significantly increases diffusion compared to seeding based on standard community detection algorithms. We also show how to use observed behaviors to estimate the intensity of peer effects.