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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2014
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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. |
format | Online Article Text |
id | pubmed-3915310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
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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