Predicting refugee flows from Ukraine with an approach to Big (Crisis) Data: a new opportunity for refugee and humanitarian studies

Abstract: Background: This paper shows that Big Data and the so-called tools of digital demography, such as Google Trends (GT) and insights from social networks such as Instagram, Twitter and Facebook, can be useful for determining, estimating, and predicting the forced migration flows to the EU caused by the war in Ukraine. Objective: The objective of this study was to test the usefulness of Google Trends indexes to predict further forced migration from Ukraine to the EU (mainly to Germany) and gain demographic insights from social networks into the age and gender structure of refugees. Methods: The primary methodological concept of our approach is to monitor the digital trace of Internet searches in Ukrainian, Russian and English with the Google Trends analytical tool (trends.google.com). Initially, keywords were chosen that are most predictive, specific, and common enough to predict the forced migration from Ukraine. We requested the data before and during the war outbreak and divided the

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource, 27 S.
• Sprache: Englisch
• Anmerkungen: Preprint

Klassifikation und Themen

• Klassifikation: Politik

Beteiligte, Orts- und Zeitangaben

• Ereignis: Veröffentlichung
• (wo): Mannheim
• (wer): SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
• (wann): 2022
• Urheber: Jurić, Tado

Weitere Informationen

• DOI: 10.1101/2022.03.15.22272428
• URN: urn:nbn:de:101:1-2023010510102744059355
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:32 MESZ