From Ukraine to the World: Using LinkedIn Data to Monitor Professional Migration from Ukraine
Margherita Bert\`e, Daniela Paolotti, Kyriaki Kalimeri

TL;DR
This study leverages LinkedIn and official refugee data to analyze the migration patterns of highly skilled Ukrainians, highlighting the pivotal role of pre-existing networks and providing insights for policy and economic strategies.
Contribution
It introduces a novel approach combining LinkedIn data with official refugee statistics to understand migration drivers and models the influence of networks on migration decisions.
Findings
LinkedIn estimates strongly correlate with UN refugee data.
Support networks are the most critical factor in destination choice.
Distance is less influential than pre-existing networks.
Abstract
Highly skilled professionals' forced migration from Ukraine was triggered by the conflict in Ukraine in 2014 and amplified by the Russian invasion in 2022. Here, we utilize LinkedIn estimates and official refugee data from the World Bank and the United Nations Refugee Agency, to understand which are the main pull factors that drive the decision-making process of the host country. We identify an ongoing and escalating exodus of educated individuals, largely drawn to Poland and Germany, and underscore the crucial role of pre-existing networks in shaping these migration flows. Key findings include a strong correlation between LinkedIn's estimates of highly educated Ukrainian displaced people and official UN refugee statistics, pointing to the significance of prior relationships with Ukraine in determining migration destinations. We train a series of multilinear regression models and the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
