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Universal patterns in egocentric communication networks
Tie strengths in social networks are heterogeneous, with strong and weak ties playing different roles at the network and individual levels. Egocentric networks, networks of relationships around an individual, exhibit few strong ties and more weaker ties, as evidenced by electronic communication reco...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10460427/ https://www.ncbi.nlm.nih.gov/pubmed/37633934 http://dx.doi.org/10.1038/s41467-023-40888-5 |
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author | Iñiguez, Gerardo Heydari, Sara Kertész, János Saramäki, Jari |
author_facet | Iñiguez, Gerardo Heydari, Sara Kertész, János Saramäki, Jari |
author_sort | Iñiguez, Gerardo |
collection | PubMed |
description | Tie strengths in social networks are heterogeneous, with strong and weak ties playing different roles at the network and individual levels. Egocentric networks, networks of relationships around an individual, exhibit few strong ties and more weaker ties, as evidenced by electronic communication records. Mobile phone data has also revealed persistent individual differences within this pattern. However, the generality and driving mechanisms of social tie strength heterogeneity remain unclear. Here, we study tie strengths in egocentric networks across multiple datasets of interactions between millions of people during months to years. We find universality in tie strength distributions and their individual-level variation across communication modes, even in channels not reflecting offline social relationships. Via a simple model of egocentric network evolution, we show that the observed universality arises from the competition between cumulative advantage and random choice, two tie reinforcement mechanisms whose balance determines the diversity of tie strengths. Our results provide insight into the driving mechanisms of tie strength heterogeneity in social networks and have implications for the understanding of social network structure and individual behavior. |
format | Online Article Text |
id | pubmed-10460427 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104604272023-08-28 Universal patterns in egocentric communication networks Iñiguez, Gerardo Heydari, Sara Kertész, János Saramäki, Jari Nat Commun Article Tie strengths in social networks are heterogeneous, with strong and weak ties playing different roles at the network and individual levels. Egocentric networks, networks of relationships around an individual, exhibit few strong ties and more weaker ties, as evidenced by electronic communication records. Mobile phone data has also revealed persistent individual differences within this pattern. However, the generality and driving mechanisms of social tie strength heterogeneity remain unclear. Here, we study tie strengths in egocentric networks across multiple datasets of interactions between millions of people during months to years. We find universality in tie strength distributions and their individual-level variation across communication modes, even in channels not reflecting offline social relationships. Via a simple model of egocentric network evolution, we show that the observed universality arises from the competition between cumulative advantage and random choice, two tie reinforcement mechanisms whose balance determines the diversity of tie strengths. Our results provide insight into the driving mechanisms of tie strength heterogeneity in social networks and have implications for the understanding of social network structure and individual behavior. Nature Publishing Group UK 2023-08-26 /pmc/articles/PMC10460427/ /pubmed/37633934 http://dx.doi.org/10.1038/s41467-023-40888-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Iñiguez, Gerardo Heydari, Sara Kertész, János Saramäki, Jari Universal patterns in egocentric communication networks |
title | Universal patterns in egocentric communication networks |
title_full | Universal patterns in egocentric communication networks |
title_fullStr | Universal patterns in egocentric communication networks |
title_full_unstemmed | Universal patterns in egocentric communication networks |
title_short | Universal patterns in egocentric communication networks |
title_sort | universal patterns in egocentric communication networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10460427/ https://www.ncbi.nlm.nih.gov/pubmed/37633934 http://dx.doi.org/10.1038/s41467-023-40888-5 |
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