Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4957560 | Pervasive and Mobile Computing | 2016 | 27 Pages |
Abstract
Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people's mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual's urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people's tendency to revisit few favorite venues using the shortest-path available.
Related Topics
Physical Sciences and Engineering
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Computer Networks and Communications
Authors
Eduardo Mucelli Rezende Oliveira, Aline Carneiro Viana, Carlos Sarraute, Jorge Brea, Ignacio Alvarez-Hamelin,