The Importance of Local Clusters for the Diffusion of Opinions and Beliefs in Interpersonal Communication Networks

Opinions and beliefs are essential ingredients in the diffusion of innovation. We present a framework to model and simulate diffusion processes of opinions and beliefs in interpersonal communication networks. We introduce an algorithm to create stylized networks with attributes of real world interpersonal communication networks. We also introduce a simple, but expandable model for simulating the dynamics of the diffusion processes of opinions and beliefs. We apply network multiagent simulations to show the importance of local clusters of connected agents for keeping opinions and beliefs endemic in a social system. We also argue that due to the structure of interpersonal networks, these local clusters have the capability to propagate opinions and ideas into the entire system.