Quantifying information flow during emergencies

Liang Gao, Chaoming Song, Ziyou Gao, Albert László Barabási, James P. Bagrow, Dashun Wang

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Article number03997
JournalScientific Reports
Volume4
DOIs
StatePublished - Feb 6 2014

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Emergencies
Communication
Cell Phones
Human Activities
Social Support
Demography

ASJC Scopus subject areas

  • General

Cite this

Gao, L., Song, C., Gao, Z., Barabási, A. L., Bagrow, J. P., & Wang, D. (2014). Quantifying information flow during emergencies. Scientific Reports, 4, [03997]. https://doi.org/10.1038/srep03997

Quantifying information flow during emergencies. / Gao, Liang; Song, Chaoming; Gao, Ziyou; Barabási, Albert László; Bagrow, James P.; Wang, Dashun.

In: Scientific Reports, Vol. 4, 03997, 06.02.2014.

Research output: Contribution to journalArticle

Gao, L, Song, C, Gao, Z, Barabási, AL, Bagrow, JP & Wang, D 2014, 'Quantifying information flow during emergencies', Scientific Reports, vol. 4, 03997. https://doi.org/10.1038/srep03997
Gao L, Song C, Gao Z, Barabási AL, Bagrow JP, Wang D. Quantifying information flow during emergencies. Scientific Reports. 2014 Feb 6;4. 03997. https://doi.org/10.1038/srep03997
Gao, Liang ; Song, Chaoming ; Gao, Ziyou ; Barabási, Albert László ; Bagrow, James P. ; Wang, Dashun. / Quantifying information flow during emergencies. In: Scientific Reports. 2014 ; Vol. 4.
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