DocumentCode :
741877
Title :
Uncovering Measurements of Social and Demographic Behavior From Smartphone Location Data
Author :
Kelly, Denis ; Smyth, Brendan ; Caulfield, Brian
Author_Institution :
Clarity Center for Sensor Web Technol., Univ. Coll. Dublin, Dublin, Ireland
Volume :
43
Issue :
2
fYear :
2013
fDate :
3/1/2013 12:00:00 AM
Firstpage :
188
Lastpage :
198
Abstract :
Human behavior, and in particular location behavior, is highly routine based. Modern mobile phones, through global position system (GPS) technology and cell tower and WiFi location identification, enable us to trace human location behavior at scales that were previously unattainable. The goal of this paper is to examine human location behavior, through mobile phone data, and investigate if links can be made between location behavior patterns and particular demographic and social characteristics about an individual. We hypothesize that an individual´s daily predictability can be key to linking their behavior to certain characteristics, and we propose predictability and geographic areas of interest models to analyze this hypothesis. Experiments reveal that measurements, which are based on our proposed location predictability models, can correctly infer 17 different characteristics about an individual with an average accuracy of 85.5%.
Keywords :
mobile handsets; smart phones; wireless LAN; WiFi location identification; cell tower; demographic behavior; global position system technology; human behavior; human location behavior; mobile phones; particular location behavior; smartphone location data; social behavior; uncovering measurements; Clustering algorithms; Couplings; Entropy; Global Positioning System; Hidden Markov models; Humans; Mobile handsets; Global positioning system (GPS); motion analysis; pattern clustering methods; pattern recognition;
fLanguage :
English
Journal_Title :
Human-Machine Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-2291
Type :
jour
DOI :
10.1109/TSMC.2013.2238926
Filename :
6461530
Link To Document :
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