Bounded confidence model on a still growing scale-free network

TL;DR

This paper investigates a bounded confidence opinion dynamics model on a growing scale-free network, comparing its behavior with fixed networks, and finds that network growth does not significantly affect opinion evolution outcomes.

Contribution

It introduces a bounded confidence model on a growing scale-free network and compares its results with fixed networks, revealing minimal impact of network growth on opinion dynamics.

Findings

Network growth does not significantly alter opinion convergence.

The model behaves similarly on growing and fixed networks.

Opinion dynamics are robust to network growth strategies.

Abstract

A Bounded Confidence (BC) model of socio-physics, in which the agents have continuous opinions and can influence each other only if the distance between their opinions is below a threshold, is simulated on a still growing scale-free network considering several different strategies: for each new node (or vertex), that is added to the network all individuals of the network have their opinions updated following a BC model recipe. The results obtained are compared with the original model, with numerical simulations on different graph structures and also when it is considered on the usual fixed BA network. In particular, the comparison with the latter leads us to conclude that it does not matter much whether the network is still growing or is fixed during the opinion dynamics.