Role of social environment and social clustering in spread of opinions in co-evolving networks

TL;DR

This study explores how social environment and clustering influence opinion spread in co-evolving networks, revealing that opinion acceptance probabilities and initial network structure lead to diverse consensus states with complex size dependence.

Contribution

It introduces modifications to the co-evolving network voter model, incorporating asymmetric influence and local clustering preferences, and analyzes their effects on opinion dynamics.

Findings

Different opinion acceptance distributions lead to diverse final network states.

Initial clustering can induce transitions between consensus and fragmented states.

Final network structures can exhibit small-world properties.

Abstract

Taking a pragmatic approach to the processes involved in the phenomena of collective opinion formation, we investigate two specific modifications to the co-evolving network voter model of opinion formation, studied by Holme and Newman [1]. First, we replace the rewiring probability parameter by a distribution of probability of accepting or rejecting opinions between individuals, accounting for the asymmetric influences in relationships among individuals in a social group. Second, we modify the rewiring step by a path-length-based preference for rewiring that reinforces local clustering. We have investigated the influences of these modifications on the outcomes of the simulations of this model. We found that varying the shape of the distribution of probability of accepting or rejecting opinions can lead to the emergence of two qualitatively distinct final states, one having several isolated connected components each in internal consensus leading to the existence of diverse set of opinions and the other having one single dominant connected component with each node within it having the same opinion. Furthermore, and more importantly, we found that the initial clustering in network can also induce similar transitions. Our investigation also brings forward that these transitions are governed by a weak and complex dependence on system size. We found that the networks in the final states of the model have rich structural properties including the small world property for some parameter regimes. [1] P. Holme and M. Newman, Phys. Rev. E 74, 056108 (2006).