Paper Info
Title
Exploring the Mobility of Mobile Phone Users
Abstract
Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datasets. In this article, we explore the connections between various features of human behavior extracted from a large mobile phone dataset. Our observations are based on the analysis of communication data of 100,000 anonymized and randomly chosen individuals in a dataset of communications in Portugal. We show that clustering and principal component analysis allow for a significant dimension reduction with limited loss of information. The most important features are related to geographical location. In particular, we observe that most people spend most of their time at only a few locations. With the help of clustering methods, we then robustly identify home and office locations and compare the results with official census data. Finally, we analyze the geographic spread of users’ frequent locations and show that commuting distances can be reasonably well explained by a gravity model.
Year
DOI
Venue
2012
10.1016/j.physa.2012.11.040
Physica A: Statistical Mechanics and its Applications
Keywords
Field
DocType
Human mobility,Data mining,Location detection,Commuting distance
Data mining,Mobile search,Location,Social network,Dimensionality reduction,Mobile phone,Gravity model of trade,Cluster analysis,Mathematics,Principal component analysis
Journal
Volume
Issue
ISSN
392
6
0378-4371
Citations 
PageRank 
References 
20
1.23
9
Authors
8
Name
Order
Citations
PageRank
Balázs Csanád Csáji19011.26
Arnaud Browet2584.79
Vincent A. Traag31079.04
Jean-Charles Delvenne429932.41
Etienne Huens5794.02
Paul van Dooren664990.48
Zbigniew Smoreda736331.18
Vincent D. Blondel81880184.86