Original Research ARTICLE
Resisting influence: How the strength of predispositions to resist control can change strategies for optimal opinion control in the voter model
- 1University of Southampton, United Kingdom
In this paper we investigate influence maximization, or optimal opinion control, in a modified version of the two-state voter dynamics in which a native state and a controlled or influenced state are accounted for. We include agent predispositions to resist influence in the form of a probability $q$ with which agents spontaneously switch back to the native state when in the controlled state. We argue that in contrast to the original voter model, optimal control in this setting depends on $q$: For low strength of predispositions $q$ optimal control should focus on hub nodes, but for large $q$ optimal control can be achieved by focusing on the lowest degree nodes. We investigate this transition between hub and low-degree node control for heterogeneous undirected networks and give analytical and numerical arguments for the existence of two control regimes.
Keywords: opinion control, voter dynamics, Scale-free Networks, optimization, Influence maximization
Received: 24 Jan 2018;
Accepted: 14 Mar 2018.
Edited by:Carlos Gershenson, Universidad Nacional Autónoma de México, Mexico
Reviewed by:Marcelo N. Kuperman, Bariloche Atomic Centre, Argentina
Genki Ichinose, Shizuoka University, Japan
Rick Quax, University of Amsterdam, Netherlands
Copyright: © 2018 Brede, Restocchi and Stein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Markus Brede, University of Southampton, Southampton, United Kingdom, email@example.com