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Understanding the Ukrainian migrants challenges in the EU: a topic modeling approach
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. National Technical University “Kharkiv Polytechnic Institute”, Kharkiv, Ukraine.ORCID-id: 0000-0002-9826-0286
Gdansk University of Technology, Gdansk, Poland.
University of the Aegean, Athens, Greece.
Gdansk University of Technology, Gdansk, Poland.
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2024 (Engelska)Ingår i: dg.o '24: Proceedings of the 25th Annual International Conference on Digital Government Research / [ed] Hsin-Chung Liao; David Duenas Cid; Marie Anne Macadar; Flavia Bernardini, Association for Computing Machinery (ACM), 2024, s. 196-205Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Confronted with the aggression against Ukraine in 2022, Europe faces one of the most important humanitarian challenges - the migration of war refugees from Ukraine, most of them women with children and the elderly. Both international institutions such as the European Union and the United Nations, but also national governments and, above all, local governments, which are the main providers of services and resources for refugees, are taking a number of measures to meet the needs. The extraordinary nature and extensive humanitarian needs pose exceptional challenges for both governments and Non-Governmental Organizations (NGOs) as well as civil society. The European countries adopted distinct reception procedures to accommodate war refugees in their territories. The purpose of this paper is to examine the challenges of war refugees from Ukraine and gain an understanding of how they vary across selected European countries. Using a text analytics approach such as BERTopic topic modeling, we analyzed text messages published on Telegram channels from February 2022 to September 2023, revealing 12 challenges facing Ukrainian migrants. Furthermore, our study delves into these challenges distribution across 6 major European countries with significant migrant populations, providing insights into regional differences. Additionally, temporal changes in 8 narrative themes in discussions of Ukrainian migration, extracted from official government websites, were examined. Together, this research contributes (1) to demonstrating how analytics-driven methodology can potentially be used to extract in-depth knowledge from textual data freely available on social media; and (2) to a deeper understanding of the various issues affecting the adaptation of Ukrainian migrants in European countries. The study also provides recommendations to improve programs and policies to better support the successful integration of Ukrainian migrants in host countries.

Ort, förlag, år, upplaga, sidor
Association for Computing Machinery (ACM), 2024. s. 196-205
Serie
ACM International Conference Proceeding Series
Nyckelord [en]
European countries, Migration challenges, Social media, Topic Modelling, Ukraine
Nationell ämneskategori
Internationell Migration och Etniska Relationer (IMER) Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:umu:diva-226180DOI: 10.1145/3657054.3657252ISI: 001238979900019Scopus ID: 2-s2.0-85195266600ISBN: 9798400709883 (digital)OAI: oai:DiVA.org:umu-226180DiVA, id: diva2:1874347
Konferens
dg.o 2024: 25th Annual International Conference on Digital Government Research, Taipei, Taiwan, June 11-14, 2024
Tillgänglig från: 2024-06-20 Skapad: 2024-06-20 Senast uppdaterad: 2025-04-24Bibliografiskt granskad

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