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Evidence for complex contagion models of social contagion from observational data

Social influence can lead to behavioural ‘fads’ that are briefly popular and quickly die out. Various models have been proposed for these phenomena, but empirical evidence of their accuracy as real-world predictive tools has so far been absent. Here we find that a ‘complex contagion’ model accuratel...

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Detalles Bibliográficos
Autores principales: Sprague, Daniel A., House, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501614/
https://www.ncbi.nlm.nih.gov/pubmed/28686719
http://dx.doi.org/10.1371/journal.pone.0180802
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author Sprague, Daniel A.
House, Thomas
author_facet Sprague, Daniel A.
House, Thomas
author_sort Sprague, Daniel A.
collection PubMed
description Social influence can lead to behavioural ‘fads’ that are briefly popular and quickly die out. Various models have been proposed for these phenomena, but empirical evidence of their accuracy as real-world predictive tools has so far been absent. Here we find that a ‘complex contagion’ model accurately describes the spread of behaviours driven by online sharing. We found that standard, ‘simple’, contagion often fails to capture both the rapid spread and the long tails of popularity seen in real fads, where our complex contagion model succeeds. Complex contagion also has predictive power: it successfully predicted the peak time and duration of the ALS Icebucket Challenge. The fast spread and longer duration of fads driven by complex contagion has important implications for activities such as publicity campaigns and charity drives.
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spelling pubmed-55016142017-07-25 Evidence for complex contagion models of social contagion from observational data Sprague, Daniel A. House, Thomas PLoS One Research Article Social influence can lead to behavioural ‘fads’ that are briefly popular and quickly die out. Various models have been proposed for these phenomena, but empirical evidence of their accuracy as real-world predictive tools has so far been absent. Here we find that a ‘complex contagion’ model accurately describes the spread of behaviours driven by online sharing. We found that standard, ‘simple’, contagion often fails to capture both the rapid spread and the long tails of popularity seen in real fads, where our complex contagion model succeeds. Complex contagion also has predictive power: it successfully predicted the peak time and duration of the ALS Icebucket Challenge. The fast spread and longer duration of fads driven by complex contagion has important implications for activities such as publicity campaigns and charity drives. Public Library of Science 2017-07-07 /pmc/articles/PMC5501614/ /pubmed/28686719 http://dx.doi.org/10.1371/journal.pone.0180802 Text en © 2017 Sprague, House http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sprague, Daniel A.
House, Thomas
Evidence for complex contagion models of social contagion from observational data
title Evidence for complex contagion models of social contagion from observational data
title_full Evidence for complex contagion models of social contagion from observational data
title_fullStr Evidence for complex contagion models of social contagion from observational data
title_full_unstemmed Evidence for complex contagion models of social contagion from observational data
title_short Evidence for complex contagion models of social contagion from observational data
title_sort evidence for complex contagion models of social contagion from observational data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501614/
https://www.ncbi.nlm.nih.gov/pubmed/28686719
http://dx.doi.org/10.1371/journal.pone.0180802
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