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Exodus 2.0: crowdsourcing geographical and social trails of mass migration

  • Troy Curry
  • Arie Croitoru
  • Andrew Crooks
  • Anthony Stefanidis
Original Article

Abstract

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.

Keywords

Refugees Forced migration Humanitarian crisis Volunteered geographic information Crowdsourcing Social media GIS Web 2.0 

JEL Classification

C800 (Data Collection and Data Estimation Methodology; Computer Programs: General) 

Notes

Acknowledgements

We would like to thank the four anonymous reviewers for providing invaluable comments and suggestions.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

10109_2018_278_MOESM1_ESM.docx (3.5 mb)
Supplementary material 1 (DOCX 3609 kb)

References

  1. Alencar A (2017) Refugee integration and social media: a local and experiential perspective. Inf Commun Soc.  https://doi.org/10.1080/1369118X.2017.1340500 CrossRefGoogle Scholar
  2. Andrade AD, Doolin B (2016) Information and communication technology and the social inclusion of refugees. Manag Inf Syst Q 40(2):405–416CrossRefGoogle Scholar
  3. Andrienko N, Andrienko G, Pelekis N, Spaccapietra S (2008) Basic concepts of movement data. In: Giannotti F, Pedreschi D (eds) Mobility, data mining and privacy—geographic knowledge discovery. Springer, Berlin, Heidelberg, pp 15–38.  https://doi.org/10.1007/978-3-540-75177-9 CrossRefGoogle Scholar
  4. Antoniou V, Fonte CC, See L, Estima J, Arsanjani JJ, Lupia F, Minghini M, Foody G, Fritz S (2016) Investigating the feasibility of geo-tagged photographs as sources of land cover input data. ISPRS Int J Geo Inf 5(5):64.  https://doi.org/10.3390/ijgi5050064 CrossRefGoogle Scholar
  5. Auer S, Bizer C, Kobilarov G, Lehmann J, Cyganiak R (2007) DBpedia: a nucleus for a web of open data. In: Auer S, Bizer C, Kobilarov G, Lehmann J, Cyganiak R, Ives Z (eds) The semantic web. Springer, New York, pp 722–735CrossRefGoogle Scholar
  6. Baker I, Card B, Raymond N (2015) Satellite imagery interpretation guide: displaced population camps. Harvard Humanitarian Initiative. Retrieved on 24 July 24 2017, from https://tinyurl.com/yayxfufo
  7. Boyd M (1989) Family and personal networks in international migration: recent developments and new agendas. Int Migrat Rev 23(3):638–670CrossRefGoogle Scholar
  8. Brekke JP, Brochmann G (2015) Stuck in transit: secondary migration of asylum seekers in Europe, national differences, and the dublin regulation. J Refug Stud 28(2):145–162CrossRefGoogle Scholar
  9. Brovelli MA, Minghini M, Kilsedar CE, Zurbarán M, Aiello M, Gianinetto M (2017) Migrate: a foss web mapping application for educating and raising awareness about migration flows in Europe. Int Arch Photogramm Remote Sens Spat Inf Sci 42(4):51–55CrossRefGoogle Scholar
  10. Charmarkeh H (2013) Social media usage, Tahriib (Migration), and settlement among Somali refugees in France. Refug Can J Refug 29 (1). https://tinyurl.com/zq3qu2z
  11. Chatfield AT, Scholl HJJ, Brajawidagda U (2013) Tsunami early warnings via twitter in government: net-savvy citizens’ co-production of time-critical public information services. Gov Inf Q 30(4):377–386CrossRefGoogle Scholar
  12. Clark L (1989) Early warning of refugee flows. Refugee Policy Group. Washington DC. Retrieved on 16 Mar 2017, from https://tinyurl.com/zr2ouax
  13. Crawley H, Duvell F, Sigona N, McMahon S, Jones K (2016) Unpacking a rapidly changing scenario: migration flows, routes and trajectories across the Mediterranean. Unravelling the Mediterranean Migration Crisis. Research brief no. 1, March 2016. Retrieved on 12 Mar 2018, from https://tinyurl.com/y8ar7jzu
  14. Cresswell T (2014) Place. In: Lee R, Castree N, Kitchin R, Lawson V, Paasi A, Philo C, Radcliff S, Roberts SM, Withers C (eds) The sage handbook of human geography. Sage, Thousand Oaks, pp 3–44CrossRefGoogle Scholar
  15. Crooks A, Pfoser D, Jenkins A, Croitoru A, Stefanidis A, Smith D, Karagiorgou S, Efentakis A, Lamprianidis G (2015) Crowdsourcing urban form and function. Int J Geogr Inf Sci 29(5):720–741CrossRefGoogle Scholar
  16. Crooks AT, Malleson N, Wise S, Heppenstall A (2018) Big data, agents and the city. In: Schintler LA, Chen Z (eds) Big data for urban and regional science. Routledge, New York, pp 204–213Google Scholar
  17. dbpedia (2017) mappings.dbpedia. Ontology Classes. Retrieved on 2 Oct 2017, from https://tinyurl.com/obzs5d7
  18. Dekker R, Engbersen G (2014) How social media transform migrant networks and facilitate migration. Glob Netw 14(4):401–418CrossRefGoogle Scholar
  19. Dijstelbloem H (2017) Migration tracking is a mess. Nature 543:32–34.  https://doi.org/10.1038/543032a CrossRefGoogle Scholar
  20. Dodge S, Weibel R, Lautenschütz AK (2008) Towards a taxonomy of movement patterns. Inf Vis 7(3–4):240–252CrossRefGoogle Scholar
  21. Dorn H, Törnros T, Zipf Z (2015) Quality evaluation of VGI using authoritative data—a comparison with land use data in Southern Germany. ISPRS Int J Geo Inf 4(3):1657–1671CrossRefGoogle Scholar
  22. Edwards S (2008) Computational tools in predicting and assessing forced migration. J Refug Stud 21(3):347–359CrossRefGoogle Scholar
  23. Eurostat (2017) Eurostat: your key to European statistics. Retrieved on 16 Mar 2017, from https://tinyurl.com/jt4q84d
  24. Flickr (2015a) Refugees charging phones at a makeshift charging station courtesy of Joshua Zakary. Retrieved on 2 Oct 2017, from https://tinyurl.com/y6woev3y
  25. Flickr (2015b) Refugees arriving at the greek island of kos courtesy of Christopher Jahn, International Federation of the Red Cross and Red Crescent. Retrieved on 2 Oct 2017, from https://tinyurl.com/y7x5wze3
  26. Fonte CC, Antoniou V, Bastin L, Estima J, Arsanjani JJ, Bayas J-CL, See L, Vatseva R (2017) Assessing VGI data quality. In: Foody G, See L, Fritz S, Mooney P, Olteanu-Raimond A-M, Fonte CC, Antoniou V (eds) Mapping and the citizen sensor. Ubiquity Press, London, pp 137–163Google Scholar
  27. Galton A (2000) Qualitative spatial change. Oxford University Press on Demand, OxfordGoogle Scholar
  28. Goodchild M (2007) Citizens as sensors: the world of volunteered geography. GeoJournal 69(4):211–221CrossRefGoogle Scholar
  29. Haklay M (2010) How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets. Environ Plan B 37(4):682–703CrossRefGoogle Scholar
  30. Hanson K (2016) Refugee crisis? There’s an app for that. Londonist. Retrieved on 3 Sept 2017, from https://tinyurl.com/y7vtp4c3
  31. Herfort B, de Albuquerque JP, Schelhorn SJ, Zipf A (2014) Exploring the geographical relations between social media and flood phenomena to improve situational awareness. In: Joaquín Huerta J, Schade S, Granell C (eds) Connecting a digital Europe through location and place. Springer, New York, pp 55–71CrossRefGoogle Scholar
  32. Houttuin S, Huson E (2016) Algeria: the new migrant staging post for Europe. IRIN: The Inside Story on Emergencies. October 25. Retrieved on 2 Oct 2017, from https://tinyurl.com/ybgwo77e
  33. Hu E (2016) An agent-based model of the European refugee crisis. GitHub repository, https://github.com/elizabethhu/refugee-abm. Retrieved on 22 Sept 2017, from https://tinyurl.com/yd5s6sjc
  34. Hübl F, Cvetojevic S, Hochmair H, Paulus G (2017) Analyzing refugee migration patterns using geo-tagged Tweets. Int J Geo Inf 6(302):1–23Google Scholar
  35. Hutchinson A (2017) Top social network demographics 2017. Social Media Today, March. Retrieved on 3 Sept 2017, from https://tinyurl.com/y75qvt7m
  36. International Organization for Migration (IOM) (2016a) Mediterranean migrant arrivals reach 358,403; Official Deaths at Sea: 4,913. December 23. Retrieved on 16 Mar 2017, from https://tinyurl.com/j6larhb
  37. International Organization for Migration (IOM) (2016b) Missing migrants project: tracking deaths along migratory routes worldwide. Retrieved on 16 Mar 2017, from https://tinyurl.com/hgus5jz
  38. Kim GH, Trimi S, Chung JH (2014) Big-data applications in the government sector. Commun ACM 57(3):78–85CrossRefGoogle Scholar
  39. Kittur A, Kraut RE (2008) Harnessing the wisdom of crowds in Wikipedia: quality through coordination. In: Proceedings of the 2008 ACM conference on computer supported cooperative work, pp 37–46Google Scholar
  40. Komito L (2011) Social media and migration: virtual community 2.0. J Am Soc Inf Sci Technol 62(6):1075–1086CrossRefGoogle Scholar
  41. Latonero M, Kift P (2018) On digital passages and borders: refugees and the new infrastructure for movement and control. Soc Media Soc.  https://doi.org/10.1177/2056305118764432 CrossRefGoogle Scholar
  42. Mabogunje AL (1970) Systems approach to a theory of rural–urban migration. Geogr Anal 2(1):1–18CrossRefGoogle Scholar
  43. Maitland C, Xu Y (2015) A social informatics analysis of refugee mobile phone use: a case study of Za’atari Syrian refugee camp. In: Proceedings of the 43rd research conference on communication, information and internet policy. Retrieved on 2 Oct 2017, from https://tinyurl.com/ydhzsl68
  44. MAPS.ME (2017) Free offline world maps. Retrieved on 10 Mar 2018, from https://tinyurl.com/y8tvkq23
  45. Miranda CO (1990) Toward a broader definition of refugee: 20th century development trends. Calif West Int Law J 20(2):9Google Scholar
  46. Mislove A, Lehmann S, Ahn YY, Onnela JP, Rosenquist JN (2011) Understanding the demographics of Twitter users. In: Proceedings of the 5th international AAAI conference on weblogs and social media (ICWSM), Barcelona, Spain, pp 554–557Google Scholar
  47. Mooney P, Minghini M (2017) A review of OpenStreetMap data. In: Foody G, See L, Fritz S, Mooney P, Olteanu-Raimond A-M, Fonte CC, Antoniou V (eds) Mapping and the citizen sensor. Ubiquity Press, London, pp 37–59Google Scholar
  48. Nathan R, Getz WM, Revilla E, Holyoak M, Kadmon R, Saltz D, Smouse PE (2008) A movement ecology paradigm for unifying organismal movement research. Proc Natl Acad Sci 105(49):19052–19059CrossRefGoogle Scholar
  49. Nature (2017) Data on movements of refugees and migrants are flawed (editorial). Nature 543:5–6.  https://doi.org/10.1038/543005b CrossRefGoogle Scholar
  50. Neis P, Zipf Z (2012) Analyzing the contributor activity of a volunteered geographic information project—the case of OenStreetMap. ISPRS Int J Geo Inf 1(3):146–165CrossRefGoogle Scholar
  51. Norris P (2001) Digital divide: civic engagement, information poverty, and the internet worldwide. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  52. O’Reilly T (2005) What is web 2.0: design patterns and business models for the next generation of software. Retrieved on 22 Sept 2017, from https://tinyurl.com/p8z24dw
  53. OpenStreetMap (2017) Za’atari refugee camp OSM object. Retrieved on 10 Mar 2018, from https://tinyurl.com/y8l9lflo
  54. OpenStreetMap Wiki (2017) Refugee camp mapping. Retrieved on 3 Sept 2017, from https://tinyurl.com/ydavj4r7
  55. Palen L, Vieweg S, Sutton J, Liu SB, Hughes AL (2007) Crisis informatics: studying crisis in a networked world. In: Proceedings of the third international conference on e-social science, Ann Arbor, MI. https://tinyurl.com/ydgl2zoh
  56. Ram A (2015) Smartphones being solace and aid to desperate refugees. Wired. Retrieved on 16 Mar 2017, from https://tinyurl.com/hpakt82
  57. Rao M (2015) A digital survival guide for the modern refugee: a compendium of helpful apps for migrants on the move. Huffington Post: The World Post. Retrieved on 24 July 2017, from https://tinyurl.com/ybuja5d7
  58. Rehrl K, Gröchenig S (2016) A framework for data-centric analysis of mapping activity in the context of volunteered geographic information. ISPRS Int J Geo Inf 5(3):37.  https://doi.org/10.3390/ijgi5030037 CrossRefGoogle Scholar
  59. ReliefWeb (2017) Syrian Arab republic dashboard. Retrieved on 24 July 2017, from https://tinyurl.com/y8buo589
  60. Sampson R, Gifford SM (2010) Place-making, settlement and well-being: the therapeutic landscapes of recently arrived youth with refugee backgrounds. Health Place 16(1):116–131CrossRefGoogle Scholar
  61. Schmeidl S (1997) Exploring the causes of forced migration: a pooled time-series analysis, 1971–1990. Soc Sci Q 78(2):284–308Google Scholar
  62. Schwartz HA, Eichstaedt JC, Kern ML, Dziurzynski L, Ramones SM, Agrawal M, Shah A, Kosinski M, Stillwell D, Seligman ME, Ungar LH (2013) Personality, gender, and age in the language of social media: the open-vocabulary approach. PLoS ONE 8(9):e73791CrossRefGoogle Scholar
  63. Sebti B (2016) 4 smartphone tools Syrian refugees use to arrive in Europe safely. Non-Government Organization. Retrieved on 16 Mar 2017, from https://tinyurl.com/jp3ks62
  64. See L, Mooney P, Foody G, Bastin L, Comber A, Estima J, Fritz S, Kerle N, Jiang B, Laakso M, Liu HY (2016) Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information. ISPRS Int J Geo Inf 5(5):55.  https://doi.org/10.3390/ijgi5050055 CrossRefGoogle Scholar
  65. Seltzer EK, Jean NS, Kramer-Golinkoff E, Asch DA, Merchant RM (2015) The content of social media’s shared images about Ebola: a retrospective study. Public Health 129(9):1273–1277CrossRefGoogle Scholar
  66. Shacknove AE (1985) Who is a refugee? Ethics 95(2):274–284CrossRefGoogle Scholar
  67. Shelton T, Poorthuis A, Graham M, Zook M (2014) Mapping the data shadows of hurricane sandy: uncovering the sociospatial dimensions of ‘big data’. Geoforum 52:167–179CrossRefGoogle Scholar
  68. Sloan L, Morgan J, Burnap P, Williams M (2015) Who Tweets? Deriving the demographic characteristics of age, occupation and social class from twitter user meta-data. PLoS ONE 10(3):e0115545CrossRefGoogle Scholar
  69. Stefanidis A, Cotnoir A, Croitoru A, Crooks A, Rice M, Radzikowski J (2013a) Demarcating new boundaries: mapping virtual polycentric communities through social media content. Cartogr Geogr Inf Sci 40(2):116–129CrossRefGoogle Scholar
  70. Stefanidis A, Crooks A, Radzikowski J (2013b) Harvesting ambient geospatial information from social media feeds. GeoJournal 78(2):319–338CrossRefGoogle Scholar
  71. Stefanidis A, Vraga E, Lamprianidis G, Radzikowski J, Delamater PL, Jacobsen KH, Pfoser D, Croitoru A, Crooks AT (2017) Zika in Twitter: temporal variations of locations, actors, and concepts. JMIR Public Health Surveill 3(2):e22CrossRefGoogle Scholar
  72. Stillwell J (1978) Interzonal migration: some historical tests of spatial-interaction models. Environ Plan A 10(10):1187–1200CrossRefGoogle Scholar
  73. Stouffer SS (1940) Intervening opportunities: a theory relating mobility and distance. Am Sociol Rev 5(6):845–867CrossRefGoogle Scholar
  74. The Migrants’ Files (2014) Counting the dead. Retrieved on 16 Mar 2017, from https://tinyurl.com/z72f6q5
  75. The World Bank (2015) The Kurdistan region of Iraq: assessing the economic and social impact of the Syrian conflict and ISIS. World Bank, Washington. Retrieved on 18 May 2018, from https://tinyurl.com/yccokqu7
  76. The World Bank (2016) The welfare of Syrian refugees: evidence from Jordan and Lebanon. World Bank, Washington. Retrieved on 18 May 2018 from https://tinyurl.com/y9v5loub
  77. The World Bank (2017a) DataBank home. Retrieved on 24 July 2017, from https://tinyurl.com/cq9guf3
  78. The World Bank (2017b) Forcibly displaced: toward a development approach supporting refugees, the internally displaced, and their hosts. World Bank, Washington.  https://doi.org/10.1596/978-1-4648-0938-5. Retrieved on 25 Sept 2017 from https://tinyurl.com/y9tnoojf
  79. Tomaszewski B (2017) GIS for refugees, by refugees. ArcNews 39(3):4–5Google Scholar
  80. United Nations Conference of Plenipotentiaries on the Status of Refugees and Stateless Persons (1951) Final act and convention relating to the status of refugees. United Nations, New YorkGoogle Scholar
  81. United Nations General Assembly (2015) Transforming our world: the 2030 agenda for sustainable development. United Nations (UN) resolution A/RES/70/1. Retrieved on 25 Sept 2017, from https://tinyurl.com/od9mens
  82. United Nations High Commissioner for Refugees (UNHCR) (2013) UNHCR statistical online population database: sources, methods and data considerations. Retrieved on 26 Mar 2018, from https://tinyurl.com/ycyzmabd
  83. United Nations High Commissioner for Refugees (UNHCR) (2016) Global trends: forced displacement in 2015. United Nations High Commissioner for Refugees (UNHCR). Retrieved on 16 Mar 2017, from https://tinyurl.com/h2uw8h5
  84. United Nations High Commissioner for Refugees (UNHCR) (2017a) UNHCR statistics: the world in numbers. Retrieved on 16 Mar 2017, from https://tinyurl.com/hks95am
  85. United Nations High Commissioner for Refugees (UNHCR) (2017b) Operational portal refugee situations: Syria regional refugee response. Retrieved on 2 Oct 2017, from https://tinyurl.com/ycd3aq96
  86. Ushahidi (2017) Read the crowd. Retrieved on 22 Sept 2017, from https://tinyurl.com/y8ydcuc3
  87. Valtonen K (2004) From the margin to the mainstream: conceptualizing refugee settlement processes. J Refug Stud 17(1):70–96CrossRefGoogle Scholar
  88. Van Deursen AJ, Van Dijk JA (2014) The digital divide shifts to differences in usage. New Med Soc 16(3):507–526CrossRefGoogle Scholar
  89. Wall M, Campbell O, Janbek D (2017) Syrian refugees and information precarity. New Med Soc 19(2):240–254CrossRefGoogle Scholar
  90. Watson I, Nagel C, Bilginsoy Z (2015) ‘Facebook refugees’ chart escape from Syria on cell phones. CNN Today. Retrieved on 2 Oct 2017, from https://tinyurl.com/y9u5nk2m
  91. Weiss-Meyer A (2017) Apps for refugees: how technology helps in a humanitarian crisis. The Atlantic, May. Retrieved on 8 Aug 2017, from https://tinyurl.com/y9nzzwsv
  92. Widener M, Horner M, Metcalf S (2013) Simulating the effects of social networks on a population’s hurricane evacuation participation. J Geogr Syst 15(2):193–209CrossRefGoogle Scholar
  93. Yang A, Fan H, Jing N (2016) Amateur or professional: assessing the expertise of major contributors in OpenStreetMap based on contributing behaviors. ISPRS Int J Geo Inf 5(2):21CrossRefGoogle Scholar
  94. Zhong C, Arisona SM, Huang X, Batty M, Schmitt G (2014) Detecting the dynamics of urban structure through spatial network analysis. Int J Geogr Inf Sci 28(11):2178–2199CrossRefGoogle Scholar
  95. Zook M, Graham M, Shelton T, Gorman S (2010) Volunteered geographic information and crowdsourcing disaster relief: a case study of the Haitian earthquake. World Med Health Policy 2(2):6–32CrossRefGoogle Scholar
  96. Zottarelli LK (1998) Determinants of refugee production: an exploratory analysis. Thesis, University of North Texas, Denton, Texas. Retrieved on 16 Mar 2017, from https://tinyurl.com/ht7jb7l

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Geography and GeoInformation ScienceGeorge Mason UniversityFairfaxUSA
  2. 2.Center for Geospatial IntelligenceGeorge Mason UniversityFairfaxUSA
  3. 3.Department of Computational and Data SciencesGeorge Mason UniversityFairfaxUSA
  4. 4.Criminal Investigations and Network Analysis (CINA) CenterGeorge Mason UniversityFairfaxUSA

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