The Impact of Network Flows on Community Formation in Models of Opinion Dynamics

Abstract

We study dynamics of opinion formation in a network of coupled agents. As the network evolves to a steady state, opinions of agents within the same community converge faster than those of other agents. This framework allows us to study how network topology and network flow, which mediates the transfer of opinions between agents, both affect the formation of communities. In traditional models of opinion dynamics, agents are coupled via conservative flows, which result in one-to-one opinion transfer. However, social interactions are often nonconservative, resulting in one-to-many transfer of opinions. We study opinion formation in networks using one-to-one and one-to-many interactions and show that they lead to different community structure within the same network.

Keywords:

• dynamic models
• mathematical modeling
• social networks

Notes

¹The specific model considered in Pluchino et al. (2006) exponentially attenuated the impact of j's opinion when it was very different from i's opinion. We consider the linear version of this model, since can be mapped to the linearized Kuramoto model, and more easily compared to nonconservative model described later in this article.