Correlating Refugee Border Crossings with Internet Search Data (bibtex)
by Kostakos, Panos, Pandya, Abhinay, Oussalah, Mourad, Hosio, Simo, Breidbach, Christoph, Kostakos, Vassilis and van Berkel, Niels
Abstract:
Can Internet search data be used as a proxy to predict refugee mobility? The soaring refugee death toll in Europe creates an urgent need for novel tools that monitor and forecast refugee flows. This study investigates the correlation between refugee mobility data and Internet search data from Google Trends. Google Trends is a freely accessible tool that provides access to Internet search data by analyzing a sample of all web queries. In our study, we surveyed refugees in Greece (entry point) and in Finland (destination point) to identify what search queries they had used during their travel. Next, we conducted time series analysis on Google search data to investigate whether interest in user-defined search queries correlated with the levels of refugee arrival data recorded by the United Nations High Commissioner for Refugees (UNHCR). Results indicate that the reuse of internet search data considerably improves the predictive power of the models.
Reference:
P. Kostakos, A. Pandya, M. Oussalah, S. Hosio, C. Breidbach, V. Kostakos, N. van Berkel, "Correlating Refugee Border Crossings with Internet Search Data", in Proceedings of the International Conference on Information Reuse and Integration for Data Science (IEEE IRI'18), 2018, 264-268.
Bibtex Entry:
@inproceedings{Kostakos2018RefugeeInternet,
	Abstract = {Can Internet search data be used as a proxy to predict refugee mobility? The soaring refugee death toll in Europe creates an urgent need for novel tools that monitor and forecast refugee flows. This study investigates the correlation between refugee mobility data and Internet search data from Google Trends. Google Trends is a freely accessible tool that provides access to Internet search data by analyzing a sample of all web queries. In our study, we surveyed refugees in Greece (entry point) and in Finland (destination point) to identify what search queries they had used during their travel. Next, we conducted time series analysis on Google search data to investigate whether interest in user-defined search queries correlated with the levels of refugee arrival data recorded by the United Nations High Commissioner for Refugees (UNHCR). Results indicate that the reuse of internet search data considerably improves the predictive power of the models.},
	Author = {Kostakos, Panos and Pandya, Abhinay and Oussalah, Mourad and Hosio, Simo and Breidbach, Christoph and Kostakos, Vassilis and van Berkel, Niels},
	Booktitle = {Proceedings of the International Conference on Information Reuse and Integration for Data Science},
	Doi = {10.1109/IRI.2018.00048},
	Location = {IEEE IRI'18},
	Pages = {264-268},
	Title = {Correlating Refugee Border Crossings with Internet Search Data},
	Type = {Conference Paper},
	Url = {https://nielsvanberkel.com/files/publications/iri2018a.pdf},
	Year = {2018}}
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