How Embeddedness and Interconnectedness Matter for Multilayer Networks

Abstract

We study social coordination among agents in a two-layer network. Using the tools of global game selection, we develop an algorithm that partitions the network into communities within which agents have the same propensity to choose the same network. We demonstrate how the topology of both networks, their correlation (measured by a multiplexing index), and the strength of network effects jointly determine agents’ social connectedness. The latter is a novel measure combining both interconnectedness and embeddedness of agents. We derive optimal targeting interventions and provide applications of our framework to technology adoption, career choice, and ethnic identity.