A two-layer model for coevolving opinion dynamics and collective decision-making in complex social systems

Abstract

Motivated by the literature on opinion dynamics and evolutionary game theory, we propose a novel mathematical framework to model the intertwined coevolution of opinions and decision-making in a complex social system. In the proposed framework, the members of a social community update their opinions and revise their actions as they learn of others' opinions shared on a communication channel, and observe of others' actions through an influence channel; these interactions determine a two-layer network structure. We offer an application of the proposed framework by tailoring it to study the adoption of a novel social norm, demonstrating that the model is able to capture the emergence of several real-world collective phenomena such as paradigm shifts and unpopular norms. Through the establishment of analytical conditions and Monte Carlo numerical simulations, we shed light on the role of the coupling between opinion dynamics and decision-making, and of the network structure, in shaping the emergence of complex collective behavior in social systems.

Opinion polarization in social networks

“…Various mathematical approaches to these problems have been proposed. Without intending to review all the pertinent literature, here we simply recall some contributions relatively close to the approach that we will adopt in this paper: microscopic models based on tracking the time evolution of the state of every node of the network (with the identification ‘node=agent’ or node=metapopulation) [11–13];mesoscopic models which incorporate a statistical description of the connectivity of the individuals to describe the time evolution of the distribution function of the social traits of interest [9,10];mesoscopic models, and corresponding macroscopic limits, in which the individuals are labelled by a variable discriminating their mutual interactions, which reproduces a (weighted) graph [14–16]. …”

“…microscopic models based on tracking the time evolution of the state of every node of the network (with the identification ‘node=agent’ or node=metapopulation) [11–13];…”

Inequality between identity groups and social unrest

“…The two main components of our utility function are material payoffs and the effects of social influences. These are the main forces driving human behaviour as studied by the two most commonly used mathematical theories in social sciences: game theory [93,[99][100][101] and social influence theory [102][103][104][105][106][107]. Our approach unifies them in a single framework leading to more realistic and comprehensive models [76,[96][97][98][108][109][110].…”

A Coevolutionary Model for Actions and Opinions in Social Networks

“…The proposed model lies at the interface between the opinion dynamics and evolutionary game literature; the dynamics of the actions and opinions are coupled seamlessly, while each separate dynamics inherits the fundamental features of their separate grounding frameworks. The effect of the network structure on a simplified version of the model with bounded rationality was investigated in [16], via numerical simulations.…”