Maintaining Ferment: On Opinion Control Over Social Networks

TL;DR

This paper develops optimal control strategies to influence opinions in social networks modeled by Friedkin-Johnsen dynamics, demonstrating the turnpike property and providing algorithms for different control objectives.

Contribution

It introduces novel optimal control formulations for opinion manipulation, leveraging Pontryagin maximum principle and turnpike properties, with algorithms and extensive numerical validation.

Findings

Control functions can steer opinions above thresholds efficiently.

Turnpike property holds for the proposed control problems.

Numerical algorithms effectively compute optimal controls.

Abstract

We consider the design of external inputs to achieve a control objective on the opinions, represented by scalars, in a social network. The opinion dynamics follow a variant of the discrete-time Friedkin-Johnsen model. We first consider two minimum cost optimal control problems over a finite interval $(T_0,T),$ $T_0 >0$ -- (1) TF where opinions at all nodes should exceed a given $\tau,$ and (2) GF where a scalar function of the opinion vector should exceed a given $\tau.$ For both problems we first provide a Pontryagin maximum principle (PMP) based control function when the controllable nodes are specified. We then show that both these problems exhibit the turnpike property where both the control function and the state vectors stay near their equilibrium for a large fraction of the time. This property is then used to choose the optimum set of controllable nodes. We then consider a third system, MF, which is a cost-constrained optimal control problem where we maximize the minimum value of a scalar function of the opinion vector over $(T_0,T).$ We provide a numerical algorithm to derive the control function for this problem using non-smooth PMP based techniques. Extensive numerical studies illustrate the three models, control techniques and corresponding outcomes.