تقرير
A geospatial bounded confidence model including mega-influencers with an application to Covid-19 vaccine hesitancy
| العنوان: | A geospatial bounded confidence model including mega-influencers with an application to Covid-19 vaccine hesitancy |
|---|---|
| المؤلفون: | Haensch, Anna, Dragovic, Natasa, Börgers, Christoph, Boghosian, Bruce |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science Mathematics Physics (Other) |
| مصطلحات موضوعية: | Computer Science - Social and Information Networks, Mathematics - Dynamical Systems, Physics - Physics and Society, I.6.3, G.3, J.4 |
| الوصف: | 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 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2210.08012 |
| رقم الأكسشن: | edsarx.2210.08012 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |