Location patterns of mobile users: A large-scale tudy.

The opportunities to understand human-mobility have increased significantly of late with the rapid adoption of wireless devices that report locations frequently. In this work1, we utilize one such rich data-set comprising of nationwide call data records from several million users to analyze and understand their location patterns. We define a location pattern as the set of locations visited by a user, which roughly speaking, can be considered to be the footprint of the user. Such an analysis is useful since it allows insight into aspects such as the range covered by a user, general direction and major routes of travel, characterization of geographic areas etc.,. These in turn are useful inputs for network planning, traffic planning and mobility models. We propose a systematic methodology that utilizes geometric structures like the Minimum Area Rectangle, line segmentation and clustering techniques to extract meaningful information for location patterns and apply it to our large data-set. Based on this we report on aspects such as the size and orientation of footprints, length of major routes as well as characterize and compare locales based on movement patterns. Finally, we identify some key features of location patterns that can be modeled very well with a single statistical distribution, the Double Pareto LogNormal (DPLN) distribution regardless of locale.