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Using advertising audience estimates to improve global development statistics​ / Ingmar Weber, Ridhi Kashyap and Emilio Zagheni

By: Contributor(s): Publication details: Geneva : International Telecommunication Union, 2018.Description: 9 pContent type:
  • texto (visual)
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  • electrónico
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  • recurso en línea
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In: ITU Journal: ICT Discoveries Vol. 2018, no. 2, p. 25-33Abstract: The United Nations Sustainable Development Goals (SDGs) are a key instrument in setting the agenda around global development until 2030. These goals come with a set of 232 indicators against which countries should monitor their progress with respect to the SDGs. Existing data sources to measure progress on the SDGs and global population trends however are often (i) outdated, (ii) lacking international comparability, (iii) lacking appropriate disaggregation, or (iv) missing completely. These problems are often especially acute among less developed countries. In this paper we describe how anonymous, aggregate data from the online advertising platforms of Facebook, LinkedIn and other services can be used in combination with existing data sources to improve global development statistics. We illustrate the process of using and validating such non-representative data through two case studies looking at (i) Internet access gender gaps, and (ii) international migration statistics.
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The United Nations Sustainable Development Goals (SDGs) are a key instrument in setting the agenda around global development until 2030. These goals come with a set of 232 indicators against which countries should monitor their progress with respect to the SDGs. Existing data sources to measure progress on the SDGs and global population trends however are often (i) outdated, (ii) lacking international comparability, (iii) lacking appropriate disaggregation, or (iv) missing completely. These problems are often especially acute among less developed countries. In this paper we describe how anonymous, aggregate data from the online advertising platforms of Facebook, LinkedIn and other services can be used in combination with existing data sources to improve global development statistics. We illustrate the process of using and validating such non-representative data through two case studies looking at (i) Internet access gender gaps, and (ii) international migration statistics.

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