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Prediction of human emergency behavior and their mobility following large-scale disaster

Published:24 August 2014Publication History

ABSTRACT

The frequency and intensity of natural disasters has significantly increased over the past decades and this trend is predicted to continue. Facing these possible and unexpected disasters, accurately predicting human emergency behavior and their mobility will become the critical issue for planning effective humanitarian relief, disaster management, and long-term societal reconstruction. In this paper, we build up a large human mobility database (GPS records of 1.6 million users over one year) and several different datasets to capture and analyze human emergency behavior and their mobility following the Great East Japan Earthquake and Fukushima nuclear accident. Based on our empirical analysis through these data, we find that human behavior and their mobility following large-scale disaster sometimes correlate with their mobility patterns during normal times, and are also highly impacted by their social relationship, intensity of disaster, damage level, government appointed shelters, news reporting, large population flow and etc. On the basis of these findings, we develop a model of human behavior that takes into account these factors for accurately predicting human emergency behavior and their mobility following large-scale disaster. The experimental results and validations demonstrate the efficiency of our behavior model, and suggest that human behavior and their movements during disasters may be significantly more predictable than previously thought.

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          cover image ACM Conferences
          KDD '14: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining
          August 2014
          2028 pages
          ISBN:9781450329569
          DOI:10.1145/2623330

          Copyright © 2014 ACM

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          • Published: 24 August 2014

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