The widespread diffusion of mobile phones and the convergence of more and more services to the mobile devices allow the service providers to collect a huge corpus of information about the behaviour of the users (e.g., location and activity), 'transforming' the cellular network into a highly distributed and pervasive sensor network. In this paper, we aim at demonstrating how, by using simple statistical tools, these data can be used to obtain information, often apparently unrelated to the mobile phone usage. To this aim, we have analysed the CDRs collected by Telecom Italia in December 2013 in Milan (Italy) and made available by the 'Open Big Data' project, to infer information about the behaviour of foreign people in Milan. Such analysis clearly highlights the potential of applying big data analysis techniques to the mobile providers data.
Inferring social information on foreign people from mobile traffic data
Callegari, Christian
;Garroppo, Rosario G.;Giordano, Stefano
2017-01-01
Abstract
The widespread diffusion of mobile phones and the convergence of more and more services to the mobile devices allow the service providers to collect a huge corpus of information about the behaviour of the users (e.g., location and activity), 'transforming' the cellular network into a highly distributed and pervasive sensor network. In this paper, we aim at demonstrating how, by using simple statistical tools, these data can be used to obtain information, often apparently unrelated to the mobile phone usage. To this aim, we have analysed the CDRs collected by Telecom Italia in December 2013 in Milan (Italy) and made available by the 'Open Big Data' project, to infer information about the behaviour of foreign people in Milan. Such analysis clearly highlights the potential of applying big data analysis techniques to the mobile providers data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.