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Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs

The structure of social networks strongly affects how different phenomena spread in human society, from the transmission of information to the propagation of contagious diseases. It is well-known that heterogeneous connectivity strongly favors spread, but a precise characterization of the redundancy...

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Autores principales: Brattig Correia, Rion, Barrat, Alain, Rocha, Luis M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9949650/
https://www.ncbi.nlm.nih.gov/pubmed/36821564
http://dx.doi.org/10.1371/journal.pcbi.1010854
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author Brattig Correia, Rion
Barrat, Alain
Rocha, Luis M.
author_facet Brattig Correia, Rion
Barrat, Alain
Rocha, Luis M.
author_sort Brattig Correia, Rion
collection PubMed
description The structure of social networks strongly affects how different phenomena spread in human society, from the transmission of information to the propagation of contagious diseases. It is well-known that heterogeneous connectivity strongly favors spread, but a precise characterization of the redundancy present in social networks and its effect on the robustness of transmission is still lacking. This gap is addressed by the metric backbone, a weight- and connectivity-preserving subgraph that is sufficient to compute all shortest paths of weighted graphs. This subgraph is obtained via algebraically-principled axioms and does not require statistical sampling based on null-models. We show that the metric backbones of nine contact networks obtained from proximity sensors in a variety of social contexts are generally very small, 49% of the original graph for one and ranging from about 6% to 20% for the others. This reflects a surprising amount of redundancy and reveals that shortest paths on these networks are very robust to random attacks and failures. We also show that the metric backbone preserves the full distribution of shortest paths of the original contact networks—which must include the shortest inter- and intra-community distances that define any community structure—and is a primary subgraph for epidemic transmission based on pure diffusion processes. This suggests that the organization of social contact networks is based on large amounts of shortest-path redundancy which shapes epidemic spread in human populations. Thus, the metric backbone is an important subgraph with regard to epidemic spread, the robustness of social networks, and any communication dynamics that depend on complex network shortest paths.
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spelling pubmed-99496502023-02-24 Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs Brattig Correia, Rion Barrat, Alain Rocha, Luis M. PLoS Comput Biol Research Article The structure of social networks strongly affects how different phenomena spread in human society, from the transmission of information to the propagation of contagious diseases. It is well-known that heterogeneous connectivity strongly favors spread, but a precise characterization of the redundancy present in social networks and its effect on the robustness of transmission is still lacking. This gap is addressed by the metric backbone, a weight- and connectivity-preserving subgraph that is sufficient to compute all shortest paths of weighted graphs. This subgraph is obtained via algebraically-principled axioms and does not require statistical sampling based on null-models. We show that the metric backbones of nine contact networks obtained from proximity sensors in a variety of social contexts are generally very small, 49% of the original graph for one and ranging from about 6% to 20% for the others. This reflects a surprising amount of redundancy and reveals that shortest paths on these networks are very robust to random attacks and failures. We also show that the metric backbone preserves the full distribution of shortest paths of the original contact networks—which must include the shortest inter- and intra-community distances that define any community structure—and is a primary subgraph for epidemic transmission based on pure diffusion processes. This suggests that the organization of social contact networks is based on large amounts of shortest-path redundancy which shapes epidemic spread in human populations. Thus, the metric backbone is an important subgraph with regard to epidemic spread, the robustness of social networks, and any communication dynamics that depend on complex network shortest paths. Public Library of Science 2023-02-23 /pmc/articles/PMC9949650/ /pubmed/36821564 http://dx.doi.org/10.1371/journal.pcbi.1010854 Text en © 2023 Brattig Correia et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Brattig Correia, Rion
Barrat, Alain
Rocha, Luis M.
Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs
title Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs
title_full Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs
title_fullStr Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs
title_full_unstemmed Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs
title_short Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs
title_sort contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9949650/
https://www.ncbi.nlm.nih.gov/pubmed/36821564
http://dx.doi.org/10.1371/journal.pcbi.1010854
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