# Opinion control in complex networks

arXiv: https://arxiv.org/abs/1412.2170 · HTML: https://mlsanity.com/paper/1412.2170/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Nov 2014.

## Built on by (most cited first, 4 of 4)

- [Aligned Alone, Misaligned Together: Forecasting Adversarial Capture in LLM Agent Populations](https://mlsanity.com/paper/2608.22444/) (2026)
- [Identifying critical nodes in complex networks by graph representation learning](https://mlsanity.com/paper/2201.07988/) (2022)
- [On the Role of Memory in Robust Opinion Dynamics](https://mlsanity.com/paper/2302.08600/) (2023)
- [Optimizing Influence Campaigns: Nudging under Bounded Confidence](https://mlsanity.com/paper/2503.18331/) (2025)

## Abstract (arXiv)

In many instances of election, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, a main goal for a party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and effects of peer-to-peer influence. Based on the exact solution of the classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method to maximize the share of the party in a social network of independent voters by pinning control strategy. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opponent party controls. We show that controlling hubs is generally a good strategy, whereas the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the independent voters are connected as directed rather than undirected networks.