Socio-Physical Approach to Consensus Building and the Occurrence of Opinion Divisions Based on External Efficacy

TL;DR

This paper introduces a new socio-physical theory of opinion dynamics on social media, explaining how consensus and divisions form influenced by external factors and opinion interactions, using a model based on the Like Bounded Confidence Model.

Contribution

It presents a novel opinion dynamics model that incorporates external pressure and contextual dependence, extending existing models like the Like Bounded Confidence Model.

Findings

The model explains how external influences affect opinion consensus and division.

It demonstrates the importance of external efficacy in opinion formation.

The theory provides a framework for analyzing opinion dynamics on social media.

Abstract

The proliferation of public networks has enabled instantaneous and interactive communication that transcends temporal and spatial constraints. The vast amount of textual data on the Web has facilitated the study of quantitative analysis of public opinion, which could not be visualized before. In this paper, we propose a new theory of opinion dynamics. This theory is designed to explain consensus building and opinion splitting in opinion exchanges on social media such as Twitter. With the spread of public networks, immediate and interactive communication that transcends temporal and spatial constraints has become possible, and research is underway to quantitatively analyze the distribution of public opinion, which has not been visualized until now, using vast amounts of text data. In this paper, we propose a model based on the Like Bounded Confidence Model, which represents opinions as continuous quantities. However, the Bounded Confidence mModel assumes that people with different opinions move without regard to their opinions, rather than ignoring them. Furthermore, our theory modeled the phenomenon in such a way that it can incorporate and represent the effects of external external pressure and dependence on surrounding conditions. This paper is a revised version of a paper submitted in December 2018(Opinion Dynamics Theory for Analysis of Consensus Formation and Division of Opinion on the Internet).