Opinion control in complex networks

TL;DR

This paper introduces a computational method to optimize opinion control in social networks by strategically pinning influential nodes, especially directed hubs, to maximize a party’s share among independent voters.

Contribution

It presents a novel optimization approach for opinion control using the classical voter model with zealots, improving control strategies over traditional hub-based methods.

Findings

Optimized control strategies outperform simple hub control.

Directed networks benefit more from the optimized approach.

Controlling hubs is effective but can be improved with optimization.

Abstract

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.