2010 · 25 citations · 8 references
Social SciencesGeographyTransportation PlanningMobile ComputingTransportTransportationMobility Pattern AnalysisMobility PatternsPopulation MobilitySocial MobilitySpatial MobilityHuman Mobility AnalysisHuman Mobility PatternsMobile Phone Mobility DataMobility Data AnalysisMobility MeasurementSocial Network CentralitySocial Network Influence
The deployment of ubiquitous computing technologies in the real-world has enabled the capture of large-scale quantitative data related to human behavior, including geographical information. This type of data creates an opportunity to characterize human mobility, with potential applications ranging from modeling the spread of viruses to transportation planning. This paper presents an initial study focused on understanding the similarities and differences in mobility patterns across countries with different economic levels. In particular, we analyze and compare human mobility in a developing and an advanced economy 1 by means of their cell phone traces. We characterize mobility in terms of (1) average distance traveled, (2) area of influence of each individual, and (3) geographic sparsity of the social network. Our results indicate that there are statistically significant differences in human mobility across countries with different economic levels. Specifically, individuals in the developing economy show smaller mobility and smaller geographical sparsity of their social network when compared to individuals in the advanced economy. 1.
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