Wisdom of Crowds Effects under Antagonistic Interactions and Correlated Opinions

TL;DR

This paper examines how collective opinion accuracy is affected by antagonistic interactions and opinion correlations in linear opinion dynamics models on signed networks, identifying conditions that enhance or hinder collective wisdom.

Contribution

It extends existing opinion dynamics models to include antagonistic interactions and correlated opinions, providing new conditions for when collective wisdom is achieved.

Findings

Identifies conditions for wisdom improvement in signed networks.

Shows how opinion correlation affects collective wisdom.

Extends models to dependent initial opinions.

Abstract

This paper investigates the wisdom of crowds of linear opinion dynamics models evolving on signed networks. Conditions are given under which models such as the DeGroot, Friedkin-Johnsen (FJ) and concatenated FJ models improve or undermine collective wisdom. The extension to dependent initial opinions is also presented, highlighting how the correlation structure influences the feasibility and geometry of the wisdom-improving regions.