xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
Ministerio de Economía, Industria y Competitividad (España) Comunidad de Madrid
Sponsor:
This work has been supported by the research project CANCAN (Content and Context based Adaptation in Mobile Networks), grant no. ANR-18-CE25-0011, funded by the French National Research Agency (ANR). The work of M.F. was partially supported by the Atracción de Talento Investigador grant no. 2019-T1/TIC-16037 NetSense, funded by Comunidad de Madrid. E.M. and I.U. acknowledge partial support by Ministerio de Economía, Industria y Competitividad, Gobierno de España, grant nos. FIS2016-78904-C3-3-P and PID2019-106811GB-C32.
Project:
Gobierno de España. FIS2016-78904-C3-3-P Gobierno de España. PID2019-106811GB-C32 Comunidad de Madrid. 2019-T1/TIC-16037/NetSense
Keywords:
Digital usage gap
,
Inequality
,
Mobile phone data
,
Development
,
Privacy-preserving
Reliable and timely information on socio-economic status and divides is critical to social and economic research and policing. Novel data sources from mobile communication platforms have enabled new cost-effective approaches and models to investigate social diReliable and timely information on socio-economic status and divides is critical to social and economic research and policing. Novel data sources from mobile communication platforms have enabled new cost-effective approaches and models to investigate social disparity, but their lack of interpretability, accuracy or scale has limited their relevance to date. We investigate the divide in digital mobile service usage with a large dataset of 3.7 billion time-stamped and geo-referenced mobile traffic records in a major European country, and find profound geographical unevenness in mobile service usage -especially on news, e-mail, social media consumption and audio/video streaming. We relate such diversity with income, educational attainment and inequality, and reveal how low-income or low-education areas are more likely to engage in video streaming or social media and less in news consumption, information searching, e-mail or audio streaming. The digital usage gap is so large that we can accurately infer the socio-economic status of a small area or even its Gini coefficient only from aggregated data traffic. Our results make the case for an inexpensive, privacy-preserving, real-time and scalable way to understand the digital usage divide and, in turn, poverty, unemployment or economic growth in our societies through mobile phone data.[+][-]