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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...

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Autores principales: Andres, Georges, Casiraghi, Giona, Vaccario, Giacomo, Schweitzer, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
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.
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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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