DocumentCode
3717234
Title
City users´ classification with mobile phone data
Author
Lorenzo Gabrielli;Barbara Furletti;Roberto Trasarti;Fosca Giannotti;Dino Pedreschi
Author_Institution
Dep. of Information Engineering, University of Pisa - Italy
fYear
2015
Firstpage
1007
Lastpage
1012
Abstract
Nowadays mobile phone data are an actual proxy for studying the users´ social life and urban dynamics. In this paper we present the Sociometer, and analytical framework aimed at classifying mobile phone users into behavioral categories by means of their call habits. The analytical process starts from spatio-temporal profiles, learns the different behaviors, and returns annotated profiles. After the description of the methodology and its evaluation, we present an application of the Sociometer for studying city users of one small and one big city, evaluating the impact of big events in these cities.
Keywords
"Cities and towns","Mobile handsets","Labeling","Iterative closest point algorithm","Robustness","Big data","Electronic mail"
Publisher
ieee
Conference_Titel
Big Data (Big Data), 2015 IEEE International Conference on
Type
conf
DOI
10.1109/BigData.2015.7363852
Filename
7363852
Link To Document