Quantifying information flow during emergencies

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

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

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
Article number3997
JournalScientific Reports
Volume4
DOIs
StatePublished - 6 Feb 2014
Externally publishedYes

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