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Quantifying Information Flow During Emergencies

Recent advances on human dynamics have focused on the normal patterns of human activities, with the quantitative understanding of human behavior under extreme events remaining a crucial missing chapter. This has a wide array of potential applications, ranging from emergency response and detection to...

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Detalles Bibliográficos
Autores principales: Gao, Liang, Song, Chaoming, Gao, Ziyou, Barabási, Albert-László, Bagrow, James P., Wang, Dashun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3915310/
https://www.ncbi.nlm.nih.gov/pubmed/24499738
http://dx.doi.org/10.1038/srep03997
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author Gao, Liang
Song, Chaoming
Gao, Ziyou
Barabási, Albert-László
Bagrow, James P.
Wang, Dashun
author_facet Gao, Liang
Song, Chaoming
Gao, Ziyou
Barabási, Albert-László
Bagrow, James P.
Wang, Dashun
author_sort Gao, Liang
collection PubMed
description Recent advances on human dynamics have focused on the normal patterns of human activities, with the quantitative understanding of human behavior under extreme events remaining a crucial missing chapter. This has a wide array of potential applications, ranging from emergency response and detection to traffic control and management. Previous studies have shown that human communications are both temporally and spatially localized following the onset of emergencies, indicating that social propagation is a primary means to propagate situational awareness. We study real anomalous events using country-wide mobile phone data, finding that information flow during emergencies is dominated by repeated communications. We further demonstrate that the observed communication patterns cannot be explained by inherent reciprocity in social networks, and are universal across different demographics.
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spelling pubmed-39153102014-02-06 Quantifying Information Flow During Emergencies Gao, Liang Song, Chaoming Gao, Ziyou Barabási, Albert-László Bagrow, James P. Wang, Dashun Sci Rep Article Recent advances on human dynamics have focused on the normal patterns of human activities, with the quantitative understanding of human behavior under extreme events remaining a crucial missing chapter. This has a wide array of potential applications, ranging from emergency response and detection to traffic control and management. Previous studies have shown that human communications are both temporally and spatially localized following the onset of emergencies, indicating that social propagation is a primary means to propagate situational awareness. We study real anomalous events using country-wide mobile phone data, finding that information flow during emergencies is dominated by repeated communications. We further demonstrate that the observed communication patterns cannot be explained by inherent reciprocity in social networks, and are universal across different demographics. Nature Publishing Group 2014-02-06 /pmc/articles/PMC3915310/ /pubmed/24499738 http://dx.doi.org/10.1038/srep03997 Text en Copyright © 2014, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Article
Gao, Liang
Song, Chaoming
Gao, Ziyou
Barabási, Albert-László
Bagrow, James P.
Wang, Dashun
Quantifying Information Flow During Emergencies
title Quantifying Information Flow During Emergencies
title_full Quantifying Information Flow During Emergencies
title_fullStr Quantifying Information Flow During Emergencies
title_full_unstemmed Quantifying Information Flow During Emergencies
title_short Quantifying Information Flow During Emergencies
title_sort quantifying information flow during emergencies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3915310/
https://www.ncbi.nlm.nih.gov/pubmed/24499738
http://dx.doi.org/10.1038/srep03997
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