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Leveraging Facebook's Advertising Platform to Monitor Stocks of Migrants
Author(s) -
Zagheni Emilio,
Weber Ingmar,
Gummadi Krishna
Publication year - 2017
Publication title -
population and development review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.836
H-Index - 96
eISSN - 1728-4457
pISSN - 0098-7921
DOI - 10.1111/padr.12102
Subject(s) - citation , population , advertising , sociology , computer science , world wide web , library science , business , demography
GIVEN THE IMPORTANCE of demographic data for monitoring development, the lack of appropriate sources and indicators for measuring progress toward the achievement of targets—like the United Nations’ “2030 Agenda for Sustainable Development”—is a significant cause of uncertainty. As part of a larger effort to tackle the issue, in 2014 the United Nations asked an independent expert advisory group to make recommendations to bring about a data revolution in sustainable development. Data innovation, like new digital traces from a variety of technologies, is seen as a significant opportunity to inform policy evaluation and to improve estimates and projections. In this article, we contribute to the development of tools and methods that leverage new data sources for demographic research. We present an innovative approach to estimate stocks of migrants using a previously untapped data source: Facebook’s advertising platform. This freely available source allows advertisers and researchers to query information about socio-demographic characteristics of Facebook users, aggregated at various levels of geographic granularity. We have three main goals: i) to present a new data source that is relevant for demographers; ii) to discuss how demographers can avoid some of the problems related to the analysis of nonrepresentative Web and social media data; and iii) to lay the foundations on which demographers and data scientists can build in the future. Our focus is on migration, but some of the broader issues that we address, like the need for small-area, timely, and disaggregated indicators, are key for other disciplines as well. In economics, for instance, quantities like the gross domestic product (GDP) are determined with a lag, and final estimates are produced only after a series of revisions. The need for timely estimates has led to the development of an area of research often referred to as nowcasting, or prediction of the present (Giannone, Reichlin, and