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Exodus 2.0: crowdsourcing geographical and social trails of mass migration

Mar 2019

  • Journal Article

Journal of Geographical Systems

The exodus of displaced populations is a recurring historical phenomenon, and the ongoing Syrian humanitarian crisis is its latest incarnation. During such mass migration events, information is an essential commodity. Of particular importance is geographical (e.g., pathways and refugee camps) and social (e.g., refugee activities and networking) information. Traditionally, such information had been produced and disseminated by authorities, but a new paradigm is emerging: Web 2.0 and mobile computing technologies enable the involved stakeholder communities to produce, access, and consume migration-related information. The purpose of this article is to put forward a new typology for understanding the factors around migration and to examine the potential of crowd-generated data—especially open data and volunteered geographic information—to study such events. Using the recent wave of migration to Europe from the Middle East and northern Africa as a case study, we examine how migration-related information can be dynamically mined and analyzed to study the migrants’ pathways from their home countries to their destination sites, as well as the conditions and activities that evolve during the migration process. These new data sources can provide a deeper and more fine-grained understanding of the migration process, often in real-time, and often through the eyes of the communities affected by it. Nevertheless, this also raises significant methodological and technical challenges for their future use associated with potential biases, data quality issues, and data processing.

Citation:

Curry, T., Croitoru, A., Crooks, A., & Stefanidis, A. (2019). Exodus 2.0: crowdsourcing geographical and social trails of mass migration. Journal of Geographical Systems, 21(1): 161-187.

Authors

  • Anthony Stefanidis
  • Troy Curry
  • Arie Croitoru
  • Andrew Crooks
Publication Download

Topics:

  • Immigration
  • Open source data
  • Social media
  • Social networks

Research Areas:

  • Spatiotemporal patterns

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