Consensus formation on adaptive networks

TL;DR

This paper explores how adaptive network structures influence consensus formation, showing that network adaptivity promotes clustering and affects the dynamics and robustness of consensus and polarization.

Contribution

It introduces and analyzes models of consensus formation on adaptive networks, highlighting the feedback between network topology and dynamical processes, which was less studied before.

Findings

Adaptive rewiring fosters cluster formation and communication among similar opinions.

Network adaptivity influences the temporal evolution of consensus and polarization.

Transitions between consensus and polarization are more robust on adaptive networks.

Abstract

The structure of a network can significantly influence the properties of the dynamical processes which take place on them. While many studies have been devoted to this influence, much less attention has been devoted to the interplay and feedback mechanisms between dynamical processes and network topology on adaptive networks. Adaptive rewiring of links can happen in real life systems such as acquaintance networks where people are more likely to maintain a social connection if their views and values are similar. In our study, we consider different variants of a model for consensus formation. Our investigations reveal that the adaptation of the network topology fosters cluster formation by enhancing communication between agents of similar opinion, though it also promotes the division of these clusters. The temporal behavior is also strongly affected by adaptivity: while, on static networks, it is influenced by percolation properties, on adaptive networks, both the early and late time evolution of the system are determined by the rewiring process. The investigation of a variant of the model reveals that the scenarios of transitions between consensus and polarized states are more robust on adaptive networks.