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Reconstructing signed relations from interaction data
Positive and negative relations play an essential role in human behavior and shape the communities we live in. Despite their importance, data about signed relations is rare and commonly gathered through surveys. Interaction data is more abundant, for instance, in the form of proximity or communicati...
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/PMC10673950/ https://www.ncbi.nlm.nih.gov/pubmed/38001327 http://dx.doi.org/10.1038/s41598-023-47822-1 |
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author | Andres, Georges Casiraghi, Giona Vaccario, Giacomo Schweitzer, Frank |
author_facet | Andres, Georges Casiraghi, Giona Vaccario, Giacomo Schweitzer, Frank |
author_sort | Andres, Georges |
collection | PubMed |
description | Positive and negative relations play an essential role in human behavior and shape the communities we live in. Despite their importance, data about signed relations is rare and commonly gathered through surveys. Interaction data is more abundant, for instance, in the form of proximity or communication data. So far, though, it could not be utilized to detect signed relations. In this paper, we show how the underlying signed relations can be extracted with such data. Employing a statistical network approach, we construct networks of signed relations in five communities. We then show that these relations correspond to the ones reported by the individuals themselves. Additionally, using inferred relations, we study the homophily of individuals with respect to gender, religious beliefs, and financial backgrounds. Finally, we study group cohesion in the analyzed communities by evaluating triad statistics in the reconstructed signed network. |
format | Online Article Text |
id | pubmed-10673950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106739502023-11-24 Reconstructing signed relations from interaction data Andres, Georges Casiraghi, Giona Vaccario, Giacomo Schweitzer, Frank Sci Rep Article Positive and negative relations play an essential role in human behavior and shape the communities we live in. Despite their importance, data about signed relations is rare and commonly gathered through surveys. Interaction data is more abundant, for instance, in the form of proximity or communication data. So far, though, it could not be utilized to detect signed relations. In this paper, we show how the underlying signed relations can be extracted with such data. Employing a statistical network approach, we construct networks of signed relations in five communities. We then show that these relations correspond to the ones reported by the individuals themselves. Additionally, using inferred relations, we study the homophily of individuals with respect to gender, religious beliefs, and financial backgrounds. Finally, we study group cohesion in the analyzed communities by evaluating triad statistics in the reconstructed signed network. Nature Publishing Group UK 2023-11-24 /pmc/articles/PMC10673950/ /pubmed/38001327 http://dx.doi.org/10.1038/s41598-023-47822-1 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Andres, Georges Casiraghi, Giona Vaccario, Giacomo Schweitzer, Frank Reconstructing signed relations from interaction data |
title | Reconstructing signed relations from interaction data |
title_full | Reconstructing signed relations from interaction data |
title_fullStr | Reconstructing signed relations from interaction data |
title_full_unstemmed | Reconstructing signed relations from interaction data |
title_short | Reconstructing signed relations from interaction data |
title_sort | reconstructing signed relations from interaction data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673950/ https://www.ncbi.nlm.nih.gov/pubmed/38001327 http://dx.doi.org/10.1038/s41598-023-47822-1 |
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