Yelena Mejova, H. Gandhi, Tejas Jivanbhai Rafaliya, Mayank Rameshbhai Sitapara, R. Kashyap, Ingmar Weber
{"title":"Measuring Subnational Digital Gender Inequality in India through Gender Gaps in Facebook Use","authors":"Yelena Mejova, H. Gandhi, Tejas Jivanbhai Rafaliya, Mayank Rameshbhai Sitapara, R. Kashyap, Ingmar Weber","doi":"10.1145/3209811.3212698","DOIUrl":null,"url":null,"abstract":"Improving 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.","PeriodicalId":256587,"journal":{"name":"Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3209811.3212698","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Improving 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.