Optimal control in opinion dynamics models: towards a unified framework

TL;DR

This paper develops a flexible optimal control framework for opinion dynamics models, aiming to mitigate fake news and polarization by understanding and influencing opinion change mechanisms.

Contribution

It introduces a unified framework for optimal control applicable to various opinion dynamics models, combining theoretical and computational methods.

Findings

Characterizes properties of optimal control in opinion models

Demonstrates framework application to classical opinion influence scenarios

Provides insights into controlling opinion polarization

Abstract

Understanding how individuals change their opinions is essential to mitigate the harmful effect of fake news and stop opinion polarization. Building upon an extremely flexible opinion dynamics model that can capture the key microscopic mechanisms of social influence, the current paper elaborates a framework to find optimal control, which, thus, can be applied to a broad set of opinion dynamics settings. Using a combination of theoretical and computational approaches, I characterize the properties of optimal control and demonstrates how the elaborated framework can be applied to specific examples, which cover the classical situations that garner remarkable attention in the literature on opinion dynamics models: assimilative influence, bounded confidence, and dissimilative influence.