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Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon

While the fighting in the Syrian civil war has mostly stopped, an estimated 5.6 million Syrians remain living in neighboring countries. Of these, an estimated 1.5 million are sheltering in Lebanon. Ongoing efforts by organizations such as UNHCR to support the refugee population are often ineffective...

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Autores principales: Fatehkia, Masoomali, del Villar, Zinnya, Koebe, Till, Letouzé, Emmanuel, Lozano, Andres, Al Feel, Roaa, Mrad, Fouad, Weber, Ingmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748280/
https://www.ncbi.nlm.nih.gov/pubmed/36532846
http://dx.doi.org/10.3389/fdata.2022.1033530
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author Fatehkia, Masoomali
del Villar, Zinnya
Koebe, Till
Letouzé, Emmanuel
Lozano, Andres
Al Feel, Roaa
Mrad, Fouad
Weber, Ingmar
author_facet Fatehkia, Masoomali
del Villar, Zinnya
Koebe, Till
Letouzé, Emmanuel
Lozano, Andres
Al Feel, Roaa
Mrad, Fouad
Weber, Ingmar
author_sort Fatehkia, Masoomali
collection PubMed
description While the fighting in the Syrian civil war has mostly stopped, an estimated 5.6 million Syrians remain living in neighboring countries. Of these, an estimated 1.5 million are sheltering in Lebanon. Ongoing efforts by organizations such as UNHCR to support the refugee population are often ineffective in reaching those most in need. According to UNHCR's 2019 Vulnerability Assessment of Syrian Refugees Report (VASyR), only 44% of the Syrian refugee families eligible for multipurpose cash assistance were provided with help, as the others were not captured in the data. In this project, we are investigating the use of non-traditional data, derived from Facebook advertising data, for population level vulnerability assessment. In a nutshell, Facebook provides advertisers with an estimate of how many of its users match certain targeting criteria, e.g., how many Facebook users currently living in Beirut are “living abroad,” aged 18–34, speak Arabic, and primarily use an iOS device. We evaluate the use of such audience estimates to describe the spatial variation in the socioeconomic situation of Syrian refugees across Lebanon. Using data from VASyR as ground truth, we find that iOS device usage explains 90% of the out-of-sample variance in poverty across the Lebanese governorates. However, evaluating predictions at a smaller spatial resolution also indicate limits related to sparsity, as Facebook, for privacy reasons, does not provide audience estimates for fewer than 1,000 users. Furthermore, comparing the population distribution by age and gender of Facebook users with that of the Syrian refugees from VASyR suggests an under-representation of Syrian women on the social media platform. This work adds to growing body of literature demonstrating the value of anonymous and aggregate Facebook advertising data for analysing large-scale humanitarian crises and migration events.
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spelling pubmed-97482802022-12-15 Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon Fatehkia, Masoomali del Villar, Zinnya Koebe, Till Letouzé, Emmanuel Lozano, Andres Al Feel, Roaa Mrad, Fouad Weber, Ingmar Front Big Data Big Data While the fighting in the Syrian civil war has mostly stopped, an estimated 5.6 million Syrians remain living in neighboring countries. Of these, an estimated 1.5 million are sheltering in Lebanon. Ongoing efforts by organizations such as UNHCR to support the refugee population are often ineffective in reaching those most in need. According to UNHCR's 2019 Vulnerability Assessment of Syrian Refugees Report (VASyR), only 44% of the Syrian refugee families eligible for multipurpose cash assistance were provided with help, as the others were not captured in the data. In this project, we are investigating the use of non-traditional data, derived from Facebook advertising data, for population level vulnerability assessment. In a nutshell, Facebook provides advertisers with an estimate of how many of its users match certain targeting criteria, e.g., how many Facebook users currently living in Beirut are “living abroad,” aged 18–34, speak Arabic, and primarily use an iOS device. We evaluate the use of such audience estimates to describe the spatial variation in the socioeconomic situation of Syrian refugees across Lebanon. Using data from VASyR as ground truth, we find that iOS device usage explains 90% of the out-of-sample variance in poverty across the Lebanese governorates. However, evaluating predictions at a smaller spatial resolution also indicate limits related to sparsity, as Facebook, for privacy reasons, does not provide audience estimates for fewer than 1,000 users. Furthermore, comparing the population distribution by age and gender of Facebook users with that of the Syrian refugees from VASyR suggests an under-representation of Syrian women on the social media platform. This work adds to growing body of literature demonstrating the value of anonymous and aggregate Facebook advertising data for analysing large-scale humanitarian crises and migration events. Frontiers Media S.A. 2022-11-30 /pmc/articles/PMC9748280/ /pubmed/36532846 http://dx.doi.org/10.3389/fdata.2022.1033530 Text en Copyright © 2022 Fatehkia, del Villar, Koebe, Letouzé, Lozano, Al Feel, Mrad and Weber. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
Fatehkia, Masoomali
del Villar, Zinnya
Koebe, Till
Letouzé, Emmanuel
Lozano, Andres
Al Feel, Roaa
Mrad, Fouad
Weber, Ingmar
Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon
title Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon
title_full Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon
title_fullStr Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon
title_full_unstemmed Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon
title_short Using Facebook advertising data to describe the socio-economic situation of Syrian refugees in Lebanon
title_sort using facebook advertising data to describe the socio-economic situation of syrian refugees in lebanon
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748280/
https://www.ncbi.nlm.nih.gov/pubmed/36532846
http://dx.doi.org/10.3389/fdata.2022.1033530
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