Controlling opinions in Deffuant model by reconfiguring the network topology

Masoud Bashari and Mohammad-R. Akbarzadeh-T

Physica A: Statistical Mechanics and its Applications, 2020, vol. 544, issue C

Abstract: This paper proposes a topology reconfiguration approach for improving the rate of convergence of opinions to the opinion of a pre-specified leader for the class of convergent Deffuant models with a limited number of links. From a systems theory perspective, this problem can be viewed as a constrained stochastic nonlinear on–off control problem. Accordingly, we first propose a deterministic version of the Deffuant model and rewrite its dynamic equations to reach a set of nonlinear state-space equations where opinions are state variables and link connectivities are inputs. For that model, we then design an on–off controller based on a short-sighted predictive control strategy that dynamically changes the topology of the network by a low computational burden process. Results confirm that the proposed control strategy reaches faster convergence rates of opinions to the leader’s opinion in comparison with the well-known Erdős–Rényi structure with a similar number of links. The proposed control strategy also provides a higher rate of link connectivity for the links that are connected to the leader. Furthermore, it is observed that if the network has a fixed topology based on the obtained rate of link connectivity, it will still have a relatively rapid convergence rate which is comparable with that of a fully connected topology.

Keywords: Deffuant model; Opinion formation; Network configuration; Predictive control; Social networks (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:544:y:2020:i:c:s0378437119319314

DOI: 10.1016/j.physa.2019.123462

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