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arXiv · 2504.06913

Controlling a Social Network of Individuals with Coevolving Actions and Opinions

Roberta Raineri·Mengbin Ye·Lorenzo Zino
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Abstract

In this paper, we consider a population of individuals who have actions and opinions, which coevolve, mutually influencing one another on a complex network structure. In particular, we formulate a control problem for this social network, in which we assume that we can inject into the network a committed minority -- a set of stubborn nodes -- with the objective of steering the population, initially at a consensus, to a different consensus state. Our study focuses on two main objectives: i) determining the conditions under which the committed minority succeeds in its goal, and ii) identifying the optimal placement for such a committed minority. After deriving general monotone convergence result for the controlled dynamics, we leverage these results to build a computationally-efficient algorithm to solve the first problem and an effective heuristics for the second problem, which we prove to be NP-complete. For both algorithms, we establish theoretical guarantees. The proposed methodology is illustrated though academic examples, and demonstrated on a real-world case study.

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Roberta Raineri, Mengbin Ye, Lorenzo Zino. 2025-04-09. Controlling a Social Network of Individuals with Coevolving Actions and Opinions. https://doi.org/10.1109/tcns.2026.3691485

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