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Influence and influenceability: global directionality in directed complex networks
Knowing which nodes are influential in a complex network and whether the network can be influenced by a small subset of nodes is a key part of network analysis. However, many traditional measures of importance focus on node level information without considering the global network architecture. We us...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10465200/ https://www.ncbi.nlm.nih.gov/pubmed/37650065 http://dx.doi.org/10.1098/rsos.221380 |
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author | Rodgers, Niall Tiňo, Peter Johnson, Samuel |
author_facet | Rodgers, Niall Tiňo, Peter Johnson, Samuel |
author_sort | Rodgers, Niall |
collection | PubMed |
description | Knowing which nodes are influential in a complex network and whether the network can be influenced by a small subset of nodes is a key part of network analysis. However, many traditional measures of importance focus on node level information without considering the global network architecture. We use the method of trophic analysis to study directed networks and show that both ‘influence’ and ‘influenceability’ in directed networks depend on the hierarchical structure and the global directionality, as measured by the trophic levels and trophic coherence, respectively. We show that in directed networks trophic hierarchy can explain: the nodes that can reach the most others; where the eigenvector centrality localizes; which nodes shape the behaviour in opinion or oscillator dynamics; and which strategies will be successful in generalized rock–paper–scissors games. We show, moreover, that these phenomena are mediated by the global directionality. We also highlight other structural properties of real networks related to influenceability, such as the pseudospectra, which depend on trophic coherence. These results apply to any directed network and the principles highlighted—that node hierarchy is essential for understanding network influence, mediated by global directionality—are applicable to many real-world dynamics. |
format | Online Article Text |
id | pubmed-10465200 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-104652002023-08-30 Influence and influenceability: global directionality in directed complex networks Rodgers, Niall Tiňo, Peter Johnson, Samuel R Soc Open Sci Mathematics Knowing which nodes are influential in a complex network and whether the network can be influenced by a small subset of nodes is a key part of network analysis. However, many traditional measures of importance focus on node level information without considering the global network architecture. We use the method of trophic analysis to study directed networks and show that both ‘influence’ and ‘influenceability’ in directed networks depend on the hierarchical structure and the global directionality, as measured by the trophic levels and trophic coherence, respectively. We show that in directed networks trophic hierarchy can explain: the nodes that can reach the most others; where the eigenvector centrality localizes; which nodes shape the behaviour in opinion or oscillator dynamics; and which strategies will be successful in generalized rock–paper–scissors games. We show, moreover, that these phenomena are mediated by the global directionality. We also highlight other structural properties of real networks related to influenceability, such as the pseudospectra, which depend on trophic coherence. These results apply to any directed network and the principles highlighted—that node hierarchy is essential for understanding network influence, mediated by global directionality—are applicable to many real-world dynamics. The Royal Society 2023-08-30 /pmc/articles/PMC10465200/ /pubmed/37650065 http://dx.doi.org/10.1098/rsos.221380 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Mathematics Rodgers, Niall Tiňo, Peter Johnson, Samuel Influence and influenceability: global directionality in directed complex networks |
title | Influence and influenceability: global directionality in directed complex networks |
title_full | Influence and influenceability: global directionality in directed complex networks |
title_fullStr | Influence and influenceability: global directionality in directed complex networks |
title_full_unstemmed | Influence and influenceability: global directionality in directed complex networks |
title_short | Influence and influenceability: global directionality in directed complex networks |
title_sort | influence and influenceability: global directionality in directed complex networks |
topic | Mathematics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10465200/ https://www.ncbi.nlm.nih.gov/pubmed/37650065 http://dx.doi.org/10.1098/rsos.221380 |
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