Back to Search Start Over

The potential of Facebook advertising data for understanding flows of people from Ukraine to the European Union.

Authors :
Minora U
Bosco C
Iacus SM
Grubanov-Boskovic S
Sermi F
Spyratos S
Source :
EPJ data science [EPJ Data Sci] 2022; Vol. 11 (1), pp. 59. Date of Electronic Publication: 2022 Dec 06.
Publication Year :
2022

Abstract

This work contributes to the discussion on how innovative data can support a fast crisis response. We use operational data from Facebook to gain useful insights on where people fleeing Ukraine following the Russian invasion are likely to be displaced, focusing on the European Union. In this context, it is extremely important to anticipate where these people are moving so that local and national authorities can better manage challenges related to their reception and integration. By means of the audience estimates provided by Facebook advertising platform, we analyse the flows of people fleeing Ukraine towards the European Union. At the fifth week since the beginning of the war, our results indicate an increase in the number of Ukrainian stocks derived from Ukrainian-speaking Facebook user estimates in all the European Union (EU) countries, with Poland registering the highest percentage share (33%) of the overall increase, followed by Germany (17%), and Czechia (15%). We assess the reliability of prewar Facebook estimates by comparison with official statistics on the Ukrainian diaspora, finding a strong correlation between the two data sources (Pearson's r = 0.9 , p < 0.0001 ). We then compare our results with data on refugees in EU countries bordering Ukraine reported by the UNHCR, and we observe a similarity in their trend. In conclusion, we show how Facebook advertising data could offer timely insights on international mobility during crises, supporting initiatives aimed at providing humanitarian assistance to the displaced people, as well as local and national authorities to better manage their reception and integration.<br />Competing Interests: Competing interestsThe authors declare that they have no competing interests.<br /> (© The Author(s) 2022.)

Details

Language :
English
ISSN :
2193-1127
Volume :
11
Issue :
1
Database :
MEDLINE
Journal :
EPJ data science
Publication Type :
Academic Journal
Accession number :
36530791
Full Text :
https://doi.org/10.1140/epjds/s13688-022-00370-6