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Quantifying information flow during emergencies.

Liang Gao1, Chaoming Song2, Ziyou Gao3

  • 11] 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.

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Human communication during emergencies is dominated by repeated contacts, not just social network reciprocity. This finding offers insights into situational awareness propagation for better emergency response and management.

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Area of Science:

  • Human dynamics
  • Social network analysis
  • Computational social science

Background:

  • Understanding human behavior during extreme events is crucial for applications like emergency response and traffic management.
  • Previous research indicates human communication is localized during emergencies, suggesting social propagation is key for situational awareness.

Purpose of the Study:

  • To quantitatively analyze human behavior and information flow during real anomalous events.
  • To investigate the mechanisms driving communication patterns in emergencies.

Main Methods:

  • Analysis of country-wide mobile phone data during anomalous events.
  • Examination of communication patterns, focusing on repeated interactions.

Main Results:

  • Information flow during emergencies is primarily driven by repeated communications.
  • Observed communication patterns are not explained by inherent social network reciprocity.
  • These patterns are consistent across diverse demographics.

Conclusions:

  • Repeated communication is a dominant factor in information dissemination during emergencies.
  • This highlights a distinct communication dynamic under extreme conditions, beyond typical social network structures.
  • Findings have implications for improving emergency response and situational awareness strategies.