Abstract

The United Nations Sustainable Development Goals (SDGs) are a global consensus on the world’s most pressing challenges. They come with a set of 232 indicators against which countries should regularly monitor their progress, ensuring that everyone is represented in up-to-date data that can be used to make decisions to improve people’s lives. However, existing data sources to measure progress on the SDGs are often outdated or lacking appropriate disaggregation. We evaluate the value that anonymous, publicly accessible advertising data from Facebook can provide in mapping socio-economic development in two low and middle income countries, the Philippines and India. Concretely, we show that audience estimates of how many Facebook users in a given location use particular device types, such as Android vs. iOS devices, or particular connection types, such as 2G vs. 4G, provide strong signals for modeling regional variation in the Wealth Index (WI), derived from the Demographic and Health Survey (DHS). We further show that, surprisingly, the predictive power of these digital connectivity features is roughly equal at both the high and low ends of the WI spectrum. Finally we show how such data can be used to create gender-disaggregated predictions, but that these predictions only appear plausible in contexts with gender equal Facebook usage, such as the Philippines, but not in contexts with large gender Facebook gaps, such as India.

Details

Title
Mapping socioeconomic indicators using social media advertising data
Author
Fatehkia, Masoomali 1 ; Tingzon, Isabelle 2 ; Orden, Ardie 2 ; Sy, Stephanie 2 ; Sekara, Vedran 3 ; Garcia-Herranz, Manuel 4 ; Weber, Ingmar 1   VIAFID ORCID Logo 

 HBKU, Qatar Computing Research Institute, Doha, Qatar (GRID:grid.452146.0) (ISNI:0000 0004 1789 3191) 
 Thinking Machines, Manila, Philippines (GRID:grid.452146.0) 
 UNICEF Innovation, New York, USA (GRID:grid.420318.c) (ISNI:0000 0004 0402 478X); IT University, Department of Computer Science, Copenhagen, Denmark (GRID:grid.32190.39) (ISNI:0000 0004 0620 5453) 
 UNICEF Innovation, New York, USA (GRID:grid.420318.c) (ISNI:0000 0004 0402 478X) 
Pages
22
Publication year
2020
Publication date
2020
Publisher
Springer Nature B.V.
e-ISSN
21931127
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3059109543
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.