A complex network model for a society with socioeconomic classes
Tipo
Artigo
Data de publicação
2022
Periódico
Mathematical Biosciences and Engineering
Citações (Scopus)
3
Autores
Licciardi A.N.
Monteiro L.H.A.
Monteiro L.H.A.
Orientador
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Programa
Resumo
© 2022 American Institute of Mathematical Sciences. All rights reserved.People's attitudes and behaviors are partially shaped by the socioeconomic class to which they belong. In this work, a model of scale-free graph is proposed to represent the daily personal contacts in a society with three social classes. In the model, the probability of having a connection between two individuals depends on their social classes and on their physical distance. Numerical simulations are performed by considering sociodemographic data from France, Peru, and Zimbabwe. For the complex networks built for these three countries, average values of node degree, shortest-path length, clustering coefficient, closeness centrality, betweenness centrality, and eigenvector centrality are computed. These numerical results are discussed by taking into account the propagation of information about COVID-19.
Descrição
Palavras-chave
Assuntos Scopus
Average values , Centrality measures , Complex network models , Node degree , Personal contacts , Scale free graph , Socio-economics , Sociodemographic data , Socioeconomic class , Zimbabwe , COVID-19 , Humans , Socioeconomic Factors