Preliminary Study on Bit-String Modelling of Opinion Formation in Complex Networks

TL;DR

This paper introduces a new bit-string model for opinion formation in complex networks, aiming to better capture the complex behaviors observed in real social opinion dynamics.

Contribution

The paper proposes a novel bit-string modeling approach that overcomes limitations of existing models in describing complex opinion behaviors.

Findings

Demonstrates the potential of the new model in revealing complex opinion evolution behaviors.

Shows the model's ability to simulate diverse social opinion formation phenomena.

Abstract

Opinion formation has been gaining increasing research interests recently, and various models have been proposed. These models, however, have their limitations, among which noticeably include (i) it is generally assumed that adjacent nodes holding similar opinions will further reduce their difference in between, while adjacent nodes holding significantly different opinions would either do nothing, or cut the link in between them; (ii) opinion mutation, which describes "opinion changes not due to neighborhood influences" in real life, is typically random. While such models enjoy their simplicity and nevertheless help reveal lots of useful insights, they lack the capability of describing many complex behaviors which we may easily observe in real life. In this paper, we propose a new bit-string modeling approach. Preliminary study on the new model demonstrates its great potentials in revealing complex behaviors of social opinion evolution and formation.