Mejova, Y.Gandhi, H.R.Rafaliya, T.J.Sitapara, M.R.Kashyap, R.Weber, I.2020-03-302020-03-302018Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies, COMPASS 2018, 2018, Vol., , pp.-https://idr.nitk.ac.in/handle/123456789/8978Improving digital literacy and reducing gender inequalities in internet access and use have been recognized as important development targets within the United Nations� Sustainable Development Goals (SDGs). Tracking progress on digital gender inequalities however is challenging due to limited gender-disaggregated data, especially in less developed country contexts and at the subnational level. We show how data obtained from social media advertising APIs can be used to generate a real-time measure of digital gender inequality. Using data from the Facebook (FB) Marketing API, we document gender gaps in FB use across Indian states and examine to what extent state-level development indicators help predict these gender gaps. Higher GDP per capita, literacy and internet penetration are associated with lower gender gaps in FB presence. These state-level development predictors however are only able to explain a small proportion (7.3%) of the overall variation in gender gaps on FB. Employment-related occupational or industry characteristics from within FB emerge as important variables associated with more gender-balanced FB use. � 2018 Copyright held by the owner/author(s).Book chapter