Multiagent Social Influence: Modeling Persuasion in Contested Social Networks
Abstract
We present the Social Influence Game (SIG), a framework for modeling adversarial persuasion in social networks with an arbitrary number of competing players. Our goal is to provide a tractable and interpretable model of contested influence that scales to large systems while capturing the structural leverage points of networks. Each player allocates influence from a fixed budget to steer opinions that evolve under DeGroot dynamics, and we prove that the resulting optimization problem is a difference-of-convex program. To enable scalability, we develop an Iterated Linear (IL) solver that approximates player objectives with linear programs. In experiments on random and archetypical networks, IL achieves solutions within 7% of nonlinear solvers while being over 10x faster, scaling to large social networks. This paper lays a foundation for asymptotic analysis of contested influence in complex networks.
Cite
@article{arxiv.2510.01481,
title = {Multiagent Social Influence: Modeling Persuasion in Contested Social Networks},
author = {Renukanandan Tumu and Cristian Ioan Vasile and Victor Preciado and Rahul Mangharam},
journal= {arXiv preprint arXiv:2510.01481},
year = {2026}
}
Comments
Accepted at the American Control Conference 2026 (ACC)