Openness leads to opinion stability and narrowness to volatility

TL;DR

This paper introduces a new opinion dynamic model based on experimental findings, showing how openness and narrowness influence opinion stability and volatility through interactions on two attitudinal dimensions.

Contribution

The paper presents a novel opinion dynamic model incorporating main and secondary dimensions, highlighting how thresholds affect opinion clustering and fluctuations.

Findings

Low attraction thresholds promote secondary opinion fluctuations.

High rejection thresholds increase opinion volatility.

Population opinions tend to form clusters with internal fluctuations.

Abstract

We propose a new opinion dynamic model based on the experiments and results of Wood et al (1996). We consider pairs of individuals discussing on two attitudinal dimensions, and we suppose that one dimension is important, the other secondary. The dynamics are mainly ruled by the level of agreement on the main dimension. If two individuals are close on the main dimension, then they attract each other on the main and on the secondary dimensions, whatever their disagreement on the secondary dimension. If they are far from each other on the main dimension, then too much proximity on the secondary dimension is uncomfortable, and generates rejection on this dimension. The proximity is defined by comparing the opinion distance with a threshold called attraction threshold on the main dimension and rejection threshold on the secondary dimension. With such dynamics, a population with opinions initially uniformly drawn evolves to a set of clusters, inside which secondary opinions fluctuate more or less depending on threshold values. We observe that a low attraction threshold favours fluctuations on the secondary dimension, especially when the rejection threshold is high. The opinion evolutions of the model can be related to some stylised facts.