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 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.
1] Systems Science Institute, State Key Laboratory of Rail Traffic Control and Safety and MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China [2] Center for Complex Network Research, Department of Physics, Northeastern University, Bosoton, MA 02115, USA.
Liang
L
Gao
Department of Physics, University of Miami, Coral Gables, FL 33146, USA.
Chaoming
C
Song
Systems Science Institute, State Key Laboratory of Rail Traffic Control and Safety and MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China.
Ziyou
Z
Gao
1] Center for Complex Network Research, Department of Physics, Northeastern University, Bosoton, MA 02115, USA [2] Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA [3] Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Albert-László
AL
Barabási
1] Department of Engineering Sciences and Applied Mathematics, Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208, USA [2] Department of Mathematics and Statistics, Vermont Advanced Computing Center, Complex Systems Center, University of Vermont, Burlington, VT 05405, USA.
James P
JP
Bagrow
IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598, USA.
Dashun
D
Wang
D040421:Cell Phone / Q000706:statistics & numerical data*; D004630:Emergencies; D058015:Health Communication / Q000379:methods*; D006801:Humans; D033181:Information Dissemination / Q000379:methods*; D012944:Social Support