Paper Info
Title
Extracting human mobility and social behavior from location-aware traces.
Abstract
The concepts of location and community are rapidly becoming key points in the design of new communication paradigms and in deploying emerging mobile computing services. The need of reliable and quantitative knowledge and predictions of some relevant information, such as which locations are enjoyed by people in their daily lives and how people aggregate within communities, advocates a realistic mobility model able to describe both the human mobility throughout locations and the human attitude to socialize within communities. Unfortunately, so far, neither the concept of location nor the concept of community has been univocally defined. In this paper, we approach the problem from the most basic of starting points, namely by analyzing the real Global Positioning System datasets of human mobility traces. On this elementary basis, the paper provides a few relevant contributions. We firstly derive a deep understanding of the term location and at the same time of the notion of community strictly related to it. Secondly, we merge the two concepts into what we call geo-community. By proceeding from real spatial data rather than from a priori reasonings, we are able to quantitatively describe geo-communities and infer the probability distributions of all the features of human behavior. Finally, not to lose social implications, we present the method to derive people sociality from geo-communities. Copyright (c) 2012 John Wiley & Sons, Ltd.
Year
DOI
Venue
2013
10.1002/wcm.2209
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
Keywords
Field
DocType
mobility,pattern analysis,contact graph,mobility model
Data science,Mobile computing,Spatial analysis,Computer security,Computer science,Sociality,A priori and a posteriori,Mobility model,Probability distribution,Global Positioning System,Socialization,Distributed computing
Journal
Volume
Issue
ISSN
13.0
SP3.0
1530-8669
Citations 
PageRank 
References 
12
0.74
18
Authors
3
Name
Order
Citations
PageRank
Matteo Zignani18513.07
Sabrina Gaito220929.64
Gian Paolo Rossi339078.09