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dc.contributor.authorArcila Calderón, Carlos 
dc.contributor.authorBircan, Tuba
dc.contributor.authorAydoğdu, Bilgeçağ
dc.contributor.authorGündüz, Bünyamin
dc.contributor.authorÖnes, Onur
dc.contributor.authorAli Salah, Albert
dc.contributor.authorSîrbu, Alina
dc.date.accessioned2026-01-19T07:55:20Z
dc.date.available2026-01-19T07:55:20Z
dc.date.issued2025
dc.identifier.citationArcila-Calderón, C., Aydoğdu, B., Bircan, T., Gündüz, B., Önes, O., Salah, A. A., & Sîrbu, A. (2025). Combining Twitter and mobile phone data to observe border-rush: the Turkish-European border opening. Journal of Computational Social Science, 8(1). https://doi.org/10.1007/S42001-024-00354-8es_ES
dc.identifier.issn2432-2725
dc.identifier.issn2432-2717
dc.identifier.urihttp://hdl.handle.net/10366/168942
dc.description.abstract[EN]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 crossborder 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.es_ES
dc.description.sponsorshipFunding H2020 Societal Challenges, 870661, Tuba Bircan, H2020 Excellent Science, 871042, Alina Sîrbu.es_ES
dc.format.mimetypeapplication/pdf
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectBig dataes_ES
dc.subjectMigration flowses_ES
dc.subjectCross-border mobilityes_ES
dc.subjectSentiment analysises_ES
dc.subjectMobile phone dataes_ES
dc.subjectTwitter dataes_ES
dc.titleCombining Twitter and mobile phone data to observe border-rush: the Turkish‑European border openinges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://link.springer.com/article/10.1007/s42001-024-00354-8es_ES
dc.subject.unesco63 Sociologíaes_ES
dc.identifier.doi10.1007/S42001-024-00354-8
dc.rights.accessRightsinfo:eu-repo/semantics/embargoedAccesses_ES
dc.journal.titleJournal of Computational Social Sciencees_ES
dc.volume.number8es_ES
dc.issue.number1es_ES
dc.page.initial1es_ES
dc.page.final25es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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