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

Autor:	Fatehkia M; Qatar Computing Research Institute, HBKU, Doha, Qatar., Del Villar Z; Data-Pop Alliance, New York City, NY, United States., Koebe T; Data-Pop Alliance, New York City, NY, United States.; Freie Universität, Berlin, Germany., Letouzé E; Data-Pop Alliance, New York City, NY, United States.; Department of Political and Social Sciences, Universitat Pompeu Fabra, Barcelona, Spain., Lozano A; Data-Pop Alliance, New York City, NY, United States., Al Feel R; UN ESCWA, Beirut, Lebanon., Mrad F; UN ESCWA, Beirut, Lebanon., Weber I; Qatar Computing Research Institute, HBKU, Doha, Qatar.; Department of Computer Science, Saarland University, Saarbrücken, Germany.
Jazyk:	angličtina
Zdroj:	Frontiers in big data [Front Big Data] 2022 Nov 30; Vol. 5, pp. 1033530. Date of Electronic Publication: 2022 Nov 30 (Print Publication: 2022).
DOI:	10.3389/fdata.2022.1033530
Abstrakt:	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. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2022 Fatehkia, del Villar, Koebe, Letouzé, Lozano, Al Feel, Mrad and Weber.)
Databáze:	MEDLINE
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