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Temporal patterns of emergency calls of a metropolitan city in China

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Listed:
  • Wang, Wenjun
  • Yuan, Ning
  • Pan, Lin
  • Jiao, Pengfei
  • Dai, Weidi
  • Xue, Guixiang
  • Liu, Dong

Abstract

Quantitative understanding of human communication behavior, one of the fundamental human activities, is of great value in many practical problems, ranging from urban planning to emergency management. Most of the recent studies have focused on human communication under normal situations. Here, we study the temporal patterns of emergency calls, which is a special kind of human communication activity under emergency circumstances, by analyzing a dataset of emergency call records that collected from a metropolitan city in China during a five year period. We find that most individuals rarely make emergency calls. The distribution of inter-call durations decays as double power law along with an exponential tail. We also discover that, comparing with the normal communication activities, the activity of calling the emergency number shows more significant characteristics of burstiness and memory. We further demonstrate that the behavior of calling the emergency number when people encounter extreme events could be explained by an event-driven memory process.

Suggested Citation

  • Wang, Wenjun & Yuan, Ning & Pan, Lin & Jiao, Pengfei & Dai, Weidi & Xue, Guixiang & Liu, Dong, 2015. "Temporal patterns of emergency calls of a metropolitan city in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 846-855.
  • Handle: RePEc:eee:phsmap:v:436:y:2015:i:c:p:846-855
    DOI: 10.1016/j.physa.2015.05.028
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    References listed on IDEAS

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    Cited by:

    1. Pankaj Dey, 2023. "On the Structure of the Intermittency of Rainfall," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1461-1472, February.
    2. Agnieszka Geras & Grzegorz Siudem & Marek Gagolewski, 2022. "Time to vote: Temporal clustering of user activity on Stack Overflow," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(12), pages 1681-1691, December.

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