A geospatial bounded confidence model including mega-influencers with an application to Covid-19 vaccine hesitancy

Autor:	Haensch, Anna, Dragovic, Natasa, Börgers, Christoph, Boghosian, Bruce
Rok vydání:	2022
Předmět:	Computer Science - Social and Information Networks Mathematics - Dynamical Systems Physics - Physics and Society I.6.3 G.3 J.4
Druh dokumentu:	Working Paper
Popis:	We introduce a geospatial bounded confidence model with mega-influencers, inspired by Hegselmann and Krause. The inclusion of geography gives rise to large-scale geospatial patterns evolving out of random initial data; that is, spatial clusters of like-minded agents emerge regardless of initialization. Mega-influencers and stochasticity amplify this effect, and soften local consensus. As an application, we consider national views on Covid-19 vaccines. For a certain set of parameters, our model yields results comparable to real survey results on vaccine hesitancy from late 2020. Comment: arXiv admin note: substantial text overlap with arXiv:2202.00630
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2210.08012 Zobrazit plný text záznamu View this record from Arxiv