Detecting and understanding big events in big cities
Furletti B., Trasarti R., Gabrielli L., Smoreda Z., Vanhoof M., Ziemlicki C.
Data mining Call data records
Recent studies have shown the great potential of big data such as mobile phone location data to model human behavior. Big data allow to analyze people presence in a territory in a fast and effective way with respect to the classical surveys (diaries or questionnaires). One of the drawbacks of these collection systems is incompleteness of the users' traces; people are localized only when they are using their phones. In this work we define a data mining method for identifying people presence and understanding the impact of big events in big cities. We exploit the ability of the Sociometer for classifying mobile phone users in mobility categories through their presence profile. The experiment in cooperation with Orange Telecom has been conduced in Paris during the event Fete de la Musique using a privacy preserving protocol.
Source: Conference on the scientific analysis of mobile phone datasets, pp. 57–59, Boston, USA, 7-10 /04/2015
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@inproceedings{oai:it.cnr:prodotti:344555,
title = {Detecting and understanding big events in big cities},
author = {Furletti B. and Trasarti R. and Gabrielli L. and Smoreda Z. and Vanhoof M. and Ziemlicki C.},
booktitle = {Conference on the scientific analysis of mobile phone datasets, pp. 57–59, Boston, USA, 7-10 /04/2015},
year = {2015}
}
0000-0003-3621-3211