Quantifying Information Flow During Emergencies

View/ Open
Author
Gao, Liang
Song, Chaoming
Gao, Ziyou
Bagrow, James P.
Wang, Dashun
Note: Order does not necessarily reflect citation order of authors.
Published Version
https://doi.org/10.1038/srep03997Metadata
Show full item recordCitation
Gao, Liang, Chaoming Song, Ziyou Gao, Albert-László Barabási, James P. Bagrow, and Dashun Wang. 2014. “Quantifying Information Flow During Emergencies.” Scientific Reports 4 (1): 3997. doi:10.1038/srep03997. http://dx.doi.org/10.1038/srep03997.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.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3915310/pdf/Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAACitable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:11879827
Collections
- HMS Scholarly Articles [18124]
Contact administrator regarding this item (to report mistakes or request changes)