Author
Abstract
The escalation of conflict in Ukraine has triggered the largest refugee crisis in Europe since WWII. As of 17 August 2022, over 6.6 million people have fled Ukraine. Large-scale efforts have been made to collect data and measure the scale of forced population displacements, and identify the major receiving countries of these population flows. Current evidence has thus focused on providing a country level representation of the unfolding refugee crisis. Less is known about the subnational patterns of population displacement within Ukraine, and potential subnational settlement areas of the continuous flow of Ukrainian refugees in major receiving countries. Highly granular geographical data in real time are critical to these ends to ensure the appropriate delivery of humanitarian assistance where it is most needed. Drawing on digital trace data from Meta-Facebook, this paper aims to identify and assess the potential settlement areas and impacts of population displacements on the demographic and economic structures of sub-national communities within and outside Ukraine. We reveal large population losses in eastern, southern and northern Ukraine, particularly Khersonska (59%), Kharkivska (55%) and Kyiv (45%), and gains in western areas, specially in Livivska (16%). We also find reductions in female and young populations across the country, and increases in male and older populations in central and western regions. We identify likely settlement areas in some countries (Poland, Czechia, Slovakia, Hungary, Italy, Germany and Spain), noting that Ukrainian refugees are less likely to remain in countries which have recorded large refugee influxes but lack of local social networks, such as Romania and Turkey. We also reveal the potential impact of refugees moving to areas with old population structures and low unemployment. Yet, these impacts appear to differ across countries.
Suggested Citation
Rowe, Francisco & Neville, Ruth & González-Leonardo, Miguel, 2022.
"Sensing Population Displacement from Ukraine Using Facebook Data: Potential Impacts and Settlement Areas,"
OSF Preprints
7n6wm_v1, Center for Open Science.
Handle:
RePEc:osf:osfxxx:7n6wm_v1
DOI: 10.31219/osf.io/7n6wm_v1
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:7n6wm_v1. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.