Open AccessA complex network model for a society with socioeconomic classes
Author(s) -
Antonio Newton Licciardi,
Luiz Henrique Alves Monteiro
Publication year - 2022
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2022317
Subject(s) - betweenness centrality , centrality , closeness , clustering coefficient , socioeconomic status , complex network , shortest path problem , node (physics) , network science , graph , network theory , social network (sociolinguistics) , mathematics , computer science , cluster analysis , statistics , theoretical computer science , sociology , combinatorics , demography , population , physics , mathematical analysis , quantum mechanics , world wide web , social media
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.