Recent advances in opinion modeling: control and social influence

TL;DR

This paper reviews recent mathematical models of opinion dynamics, emphasizing optimal control and social influence factors like conviction and network connections, to better understand and potentially guide opinion formation.

Contribution

It introduces recent advancements in opinion modeling, focusing on optimal control strategies and social factors affecting opinion exchange in multi-agent systems.

Findings

Optimal control methods can steer opinion formation effectively.

Social factors like conviction and network size significantly impact opinion dynamics.

Mathematical models incorporating social aspects provide deeper insights into opinion evolution.

Abstract

We survey some recent developments on the mathematical modeling of opinion dynamics. After an introduction on opinion modeling through interacting multi-agent systems described by partial differential equations of kinetic type, we focus our attention on two major advancements: optimal control of opinion formation and influence of additional social aspects, like conviction and number of connections in social networks, which modify the agents' role in the opinion exchange process.