Extracting Relevant Information from Big Data to Anticipate Forced Migration

  • Jiashu ZhaoEmail author
  • Susan McGrath
  • Jimmy Xiangji HuangEmail author
  • Jianhong Wu
  • Shicheng Wu
Part of the Studies in Big Data book series (SBD, volume 27)


In this paper, we investigate how to extract the relevant information for forced migration from big data. Data-driven approaches have the potential to provide humanitarian agencies with real-time decision-making tools. However, very few humanitarian organisations have been able to gather, analyze and employ the data to its full potential due to capacity limitations.



This research is supported by the Social Sciences and Humanities Research Council of Canada (SSHRC) Partnership Development Grants (PDG) and the Natural Sciences and Engineering Research Council of Canada (NSERC) Collaborative Research and Training Experience Program (CREATE). We thank the anonymous reviewers for their through comments.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Centre for Refugee StudiesYork UniversityTorontoCanada
  2. 2.School of Information TechnologyYork UniversityTorontoCanada
  3. 3.Department of Mathematics and StatisticsYork UniversityTorontoCanada

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