Evidence map›Paper›PMID 36532846›Full record

ArticleFrontiers in big data2022

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

Masoomali Fatehkia, Zinnya Del Villar, Till Koebe, Emmanuel Letouzé, Andres Lozano, Roaa Al Feel, Fouad Mrad, Ingmar Weber

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Article in Frontiers in big data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Masoomali FatehkiaQatar Computing Research Institute, HBKU, Doha, Qatar.
Zinnya Del VillarData-Pop Alliance, New York City, NY, United States.
Till KoebeData-Pop Alliance, New York City, NY, United States.
Emmanuel LetouzéData-Pop Alliance, New York City, NY, United States.
Andres LozanoData-Pop Alliance, New York City, NY, United States.
Roaa Al FeelUN ESCWA, Beirut, Lebanon.
Fouad MradUN ESCWA, Beirut, Lebanon.
Ingmar WeberQatar Computing Research Institute, HBKU, Doha, Qatar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

big dataFacebook advertising dataLebanonSyrian civil warvulnerability assessment

Identifiers

PMID36532846
PMCPMC9748280

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.