TY - GEN
T1 - The relative value of facebook advertising data for poverty mapping
AU - Fatehkia, Masoomali
AU - Coles, Benjamin
AU - Ofli, Ferda
AU - Weber, Ingmar
N1 - Publisher Copyright:
Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2020
Y1 - 2020
N2 - Having reliable and up-to-date poverty data is a prerequisite for monitoring the United Nations Sustainable Development Goals (SDGs) and for planning effective poverty reduction interventions. Unfortunately, traditional data sources are often outdated or lacking appropriate disaggregation. As a remedy, satellite imagery has recently become prominent in obtaining geographically-fine-grained and up-to-date poverty estimates. Satellite data can pick up signals of economic activity by detecting light at night, it can pick up development status by detecting infrastructure such as roads, and it can pick up signals for individual household wealth by detecting different building footprints and roof types. It can, however, not look inside the households and pick up signals from individuals. On the other hand, alternative data sources such as audience estimates from Facebook's advertising platform provide insights into the devices and internet connection types used by individuals in different locations. Previous work has shown the value of such anonymous, publicly-accessible advertising data from Facebook for studying migration, gender gaps, crime rates, and health, among others. In this work, we evaluate the added value of using Facebook data over satellite data for mapping socioeconomic development in two low and middle income countries - the Philippines and India. We show that Facebook features perform roughly similar to satellite data in the Philippines with value added for urban locations. In India, however, where Facebook penetration is lower, satellite data perform better.
AB - Having reliable and up-to-date poverty data is a prerequisite for monitoring the United Nations Sustainable Development Goals (SDGs) and for planning effective poverty reduction interventions. Unfortunately, traditional data sources are often outdated or lacking appropriate disaggregation. As a remedy, satellite imagery has recently become prominent in obtaining geographically-fine-grained and up-to-date poverty estimates. Satellite data can pick up signals of economic activity by detecting light at night, it can pick up development status by detecting infrastructure such as roads, and it can pick up signals for individual household wealth by detecting different building footprints and roof types. It can, however, not look inside the households and pick up signals from individuals. On the other hand, alternative data sources such as audience estimates from Facebook's advertising platform provide insights into the devices and internet connection types used by individuals in different locations. Previous work has shown the value of such anonymous, publicly-accessible advertising data from Facebook for studying migration, gender gaps, crime rates, and health, among others. In this work, we evaluate the added value of using Facebook data over satellite data for mapping socioeconomic development in two low and middle income countries - the Philippines and India. We show that Facebook features perform roughly similar to satellite data in the Philippines with value added for urban locations. In India, however, where Facebook penetration is lower, satellite data perform better.
UR - https://www.scopus.com/pages/publications/85099586022
M3 - Conference contribution
AN - SCOPUS:85099586022
T3 - Proceedings of the 14th International AAAI Conference on Web and Social Media, ICWSM 2020
SP - 934
EP - 938
BT - Proceedings of the 14th International AAAI Conference on Web and Social Media, ICWSM 2020
PB - AAAI Press
T2 - 14th International AAAI Conference on Web and Social Media, ICWSM 2020
Y2 - 8 June 2020 through 11 June 2020
ER -