@conference {1548825, title = {The Relative Value of Facebook Advertising Data for Poverty Mapping}, booktitle = {IJCAI 2021 Workshop on AI for Social Good}, year = {2021}, abstract = {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. Un- fortunately, traditional data sources are often out- dated 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 house- holds and pick up signals from individuals. On the other hand, alternative data sources such as audience estimates from Facebook{\textquoteright}s advertising plat- form provide insights into the devices and inter- net connection types used by individuals in differ- ent 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 Face- book data over satellite data for mapping socioeconomic development in two low and middle income countries {\textendash} the Philippines and India. We show that Facebook features perform roughly similar to satellite data in the Philippines with value added for ur- ban locations. In India, however, where Facebook penetration is lower, satellite data perform better.}, author = {Masoomali Fatehkia and Benjamin Coles and Ferda Ofli and Ingmar Weber} }