{"ID":2862354,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.01481","arxiv_id":"2510.01481","title":"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.","short_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 n...","url_abs":"https://arxiv.org/abs/2510.01481","url_pdf":"https://arxiv.org/pdf/2510.01481v2","authors":"[\"Renukanandan Tumu\",\"Cristian Ioan Vasile\",\"Victor Preciado\",\"Rahul Mangharam\"]","published":"2025-10-01T21:50:09Z","proceeding":"cs.SI","tasks":"[\"cs.SI\",\"eess.SY\"]","methods":"[]","has_code":false}