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 multi-agent 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.