Titre :

Towards control of opinion diversity by introducing zealots into a polarised social group

Auteur(s) :

Vendeville, Antoine [Auteur]
Department of Computer science [University College of London] [UCL-CS]
The Inria London Programme [Inria-London]
Guedj, Benjamin [Auteur]
University College of London [London] [UCL]
Department of Computer science [University College of London] [UCL-CS]
Inria-CWI [Inria-CWI]
MOdel for Data Analysis and Learning [MODAL]
The Inria London Programme [Inria-London]
Zhou, Shi [Auteur]
Department of Computer science [University College of London] [UCL-CS]

Titre de la manifestation scientifique :

Complex Networks and Their Applications X

Ville :

Madrid

Pays :

Espagne

Date de début de la manifestation scientifique :

2021-11-30

Discipline(s) HAL :

Informatique [cs]/Réseaux sociaux et d'information [cs.SI]
Statistiques [stat]/Machine Learning [stat.ML]
Informatique [cs]/Apprentissage [cs.LG]

Résumé en anglais : [en]

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 ...
Lire la suite >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.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL