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Communities in world input-output network: Robustness and rankings

We introduce a method for assessing the robustness of community detection and apply it to a world input-output network (WION) to obtain economically plausible results. This method enabled us to rank communities in the WION in terms of their robustness and stability. The algorithmic assignment variab...

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Autores principales: Kireyev, Alexei, Leonidov, Andrey, Radionov, Stanislav, Vasilyeva, Ekaterina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9037945/
https://www.ncbi.nlm.nih.gov/pubmed/35468139
http://dx.doi.org/10.1371/journal.pone.0264623
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author Kireyev, Alexei
Leonidov, Andrey
Radionov, Stanislav
Vasilyeva, Ekaterina
author_facet Kireyev, Alexei
Leonidov, Andrey
Radionov, Stanislav
Vasilyeva, Ekaterina
author_sort Kireyev, Alexei
collection PubMed
description We introduce a method for assessing the robustness of community detection and apply it to a world input-output network (WION) to obtain economically plausible results. This method enabled us to rank communities in the WION in terms of their robustness and stability. The algorithmic assignment variability index proposed in this study is shown to have predictive power in terms of forthcoming community rearrangement. We also provide several new approaches for identifying key economic communities. These approaches are based on the application of several centrality measures to a synthetic network in which nodes represent WION communities. Using these methods, we show that in 2000–2014, United States and Japan-centered communities demonstrated decreasing trends, while the importance of the China-centered community predominantly increased. A notable feature of the Germany-centered community rank evolution is that its influence grew only as a result of the inclusion of the Netherlands and Belgium in 2013.
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spelling pubmed-90379452022-04-26 Communities in world input-output network: Robustness and rankings Kireyev, Alexei Leonidov, Andrey Radionov, Stanislav Vasilyeva, Ekaterina PLoS One Research Article We introduce a method for assessing the robustness of community detection and apply it to a world input-output network (WION) to obtain economically plausible results. This method enabled us to rank communities in the WION in terms of their robustness and stability. The algorithmic assignment variability index proposed in this study is shown to have predictive power in terms of forthcoming community rearrangement. We also provide several new approaches for identifying key economic communities. These approaches are based on the application of several centrality measures to a synthetic network in which nodes represent WION communities. Using these methods, we show that in 2000–2014, United States and Japan-centered communities demonstrated decreasing trends, while the importance of the China-centered community predominantly increased. A notable feature of the Germany-centered community rank evolution is that its influence grew only as a result of the inclusion of the Netherlands and Belgium in 2013. Public Library of Science 2022-04-25 /pmc/articles/PMC9037945/ /pubmed/35468139 http://dx.doi.org/10.1371/journal.pone.0264623 Text en © 2022 Kireyev 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
Kireyev, Alexei
Leonidov, Andrey
Radionov, Stanislav
Vasilyeva, Ekaterina
Communities in world input-output network: Robustness and rankings
title Communities in world input-output network: Robustness and rankings
title_full Communities in world input-output network: Robustness and rankings
title_fullStr Communities in world input-output network: Robustness and rankings
title_full_unstemmed Communities in world input-output network: Robustness and rankings
title_short Communities in world input-output network: Robustness and rankings
title_sort communities in world input-output network: robustness and rankings
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9037945/
https://www.ncbi.nlm.nih.gov/pubmed/35468139
http://dx.doi.org/10.1371/journal.pone.0264623
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AT vasilyevaekaterina communitiesinworldinputoutputnetworkrobustnessandrankings