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Threshold Learning Dynamics in Social Networks
Social learning is defined as the ability of a population to aggregate information, a process which must crucially depend on the mechanisms of social interaction. Consumers choosing which product to buy, or voters deciding which option to take with respect to an important issue, typically confront e...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3103531/ https://www.ncbi.nlm.nih.gov/pubmed/21637714 http://dx.doi.org/10.1371/journal.pone.0020207 |
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author | González-Avella, Juan Carlos Eguíluz, Victor M. Marsili, Matteo Vega-Redondo, Fernado San Miguel, Maxi |
author_facet | González-Avella, Juan Carlos Eguíluz, Victor M. Marsili, Matteo Vega-Redondo, Fernado San Miguel, Maxi |
author_sort | González-Avella, Juan Carlos |
collection | PubMed |
description | Social learning is defined as the ability of a population to aggregate information, a process which must crucially depend on the mechanisms of social interaction. Consumers choosing which product to buy, or voters deciding which option to take with respect to an important issue, typically confront external signals to the information gathered from their contacts. Economic models typically predict that correct social learning occurs in large populations unless some individuals display unbounded influence. We challenge this conclusion by showing that an intuitive threshold process of individual adjustment does not always lead to such social learning. We find, specifically, that three generic regimes exist separated by sharp discontinuous transitions. And only in one of them, where the threshold is within a suitable intermediate range, the population learns the correct information. In the other two, where the threshold is either too high or too low, the system either freezes or enters into persistent flux, respectively. These regimes are generally observed in different social networks (both complex or regular), but limited interaction is found to promote correct learning by enlarging the parameter region where it occurs. |
format | Text |
id | pubmed-3103531 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-31035312011-06-02 Threshold Learning Dynamics in Social Networks González-Avella, Juan Carlos Eguíluz, Victor M. Marsili, Matteo Vega-Redondo, Fernado San Miguel, Maxi PLoS One Research Article Social learning is defined as the ability of a population to aggregate information, a process which must crucially depend on the mechanisms of social interaction. Consumers choosing which product to buy, or voters deciding which option to take with respect to an important issue, typically confront external signals to the information gathered from their contacts. Economic models typically predict that correct social learning occurs in large populations unless some individuals display unbounded influence. We challenge this conclusion by showing that an intuitive threshold process of individual adjustment does not always lead to such social learning. We find, specifically, that three generic regimes exist separated by sharp discontinuous transitions. And only in one of them, where the threshold is within a suitable intermediate range, the population learns the correct information. In the other two, where the threshold is either too high or too low, the system either freezes or enters into persistent flux, respectively. These regimes are generally observed in different social networks (both complex or regular), but limited interaction is found to promote correct learning by enlarging the parameter region where it occurs. Public Library of Science 2011-05-27 /pmc/articles/PMC3103531/ /pubmed/21637714 http://dx.doi.org/10.1371/journal.pone.0020207 Text en Gonzalez et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article González-Avella, Juan Carlos Eguíluz, Victor M. Marsili, Matteo Vega-Redondo, Fernado San Miguel, Maxi Threshold Learning Dynamics in Social Networks |
title | Threshold Learning Dynamics in Social Networks |
title_full | Threshold Learning Dynamics in Social Networks |
title_fullStr | Threshold Learning Dynamics in Social Networks |
title_full_unstemmed | Threshold Learning Dynamics in Social Networks |
title_short | Threshold Learning Dynamics in Social Networks |
title_sort | threshold learning dynamics in social networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3103531/ https://www.ncbi.nlm.nih.gov/pubmed/21637714 http://dx.doi.org/10.1371/journal.pone.0020207 |
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