TY  - JOUR
PY  - 2014//
TI  - Quantifying information flow during emergencies
JO  - Scientific reports
A1  - Gao, Liang
A1  - Song, Chaoming
A1  - Gao, Ziyou
A1  - Barabási, Albert-László
A1  - Bagrow, James P.
A1  - Wang, Dashun
SP  - 3997
EP  - 3997
VL  - 4
IS  - 
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 2045-2322
UR  - http://dx.doi.org/10.1038/srep03997
ID  - ref1
ER  -