Combining Twitter and mobile phone data to observe border-rush: the Turkish-European border opening

Carlos Arcila-Calderón, Bilgeçağ Aydoğdu, Tuba Bircan (), Bünyamin Gündüz, Onur Önes, Albert Ali Salah and Alina Sîrbu
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Carlos Arcila-Calderón: University of Salamanca
Bilgeçağ Aydoğdu: Utrecht University
Tuba Bircan: Vrije Universiteit Brussel
Bünyamin Gündüz: Turkcell Technology
Onur Önes: Turkcell Technology
Albert Ali Salah: Utrecht University
Alina Sîrbu: University of Pisa

Journal of Computational Social Science, 2025, vol. 8, issue 1, No 26, 25 pages

Abstract: Abstract Following Turkey’s 2020 decision to revoke border controls, many individuals journeyed towards the Greek, Bulgarian, and Turkish borders. However, the lack of verifiable statistics on irregular migration and discrepancies between media reports and actual migration patterns require further exploration. The objective of this study is to investigate the potential of novel data sources, specifically mobile phone and Twitter data, to address this knowledge gap and to construct estimators of cross-border mobility for an improved evaluation of the unfolding events. By employing a migration diplomacy framework, we analyse mobility patterns at the border emerging from the data. Our findings demonstrate the benefits and limitations of these two data sources for both quantitative and qualitative analysis. We also discuss how mobile data and social media sources can be gainfully combined and used for research into the socio-political facets of human mobility, such as sentiment associated with it. We underscore the ethical implications of leveraging big data, particularly considering the vulnerability of the population under study. Our work contributes to a more nuanced understanding of migration dynamics and paves the way for the formulation of regulations that preclude misuse and oppressive surveillance, thereby ensuring a more accurate representation of migration realities.

Keywords: Big data; Migration flows; Cross-border mobility; Sentiment analysis; Mobile phone data; Twitter data (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s42001-024-00354-8

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