Communication regimes in opinion dynamics: Changing the number of communicating agents

TL;DR

This paper introduces communication regimes in opinion dynamics models, unifies two major models through a new parameter, and analyzes how the number of communicating agents and self-support influence opinion evolution.

Contribution

It develops a unified model covering Deffuant-Weisbuch and Krause-Hegselmann models, incorporating communication regimes and a convergence criterion.

Findings

Number of communicating agents significantly affects opinion convergence.

Self-support parameter influences the speed and stability of opinions.

A theoretical criterion for halting simulations and extrapolating results is proposed.

Abstract

This article contributes in four ways to the research on time-discrete continuous opinion dynamics with compromising agents. First, communication regimes are introduced as an elementary concept of opinion dynamic models. Second, we develop a model that covers two major models of continuous opinion dynamics, i.e. the basic model of Deffuant and Weisbuch as well as the model of Krause and Hegselmann. To combine these models, which handle different numbers of communicating agents, we convert the convergence parameter of Deffuant and Weisbuch into a parameter called self-support. Third, we present simulation results that shed light on how the number of communicating agents but also how the self-support affect opinion dynamics. The fourth contribution is a theoretically driven criterion when to stop a simulation and how to extrapolate to infinite many steps.