TL;DR
This paper presents a method to control opinion diversity in polarized social groups by strategically introducing zealots, using a mathematical model to predict and influence the group's average opinion.
Contribution
It provides a closed-form expression for the equilibrium opinion and a strategy to inject zealots to steer opinions, accounting for potential backfire effects.
Findings
Closed-form expression for average opinion at equilibrium
Strategy for zealot injection to shift opinions
Numerical validation on synthetic data
Abstract
We explore a method to influence or even control the diversity of opinions within a polarised social group. We leverage the voter model in which users hold binary opinions and repeatedly update their beliefs based on others they connect with. Stubborn agents who never change their minds ("zealots") are also disseminated through the network, which is modelled by a connected graph. Building on earlier results, we provide a closed-form expression for the average opinion of the group at equilibrium. This leads us to a strategy to inject zealots into a polarised network in order to shift the average opinion towards any target value. We account for the possible presence of a backfire effect, which may lead the group to react negatively and reinforce its level of polarisation in response. Our results are supported by numerical experiments on synthetic data.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
