From centre to centres: polycentric structures in individual mobility

Abstract

The availability of large-scale datasets collected via mobile phones has opened up opportunities to study human mobility at an individual level. The granular nature of these datasets calls for the design of summary statistics that can be used to describe succinctly mobility patterns. In this work, we show that the radius of gyration, a popular summary statistic to quantify the extent of an individual's whereabouts, suffers from a sensitivity to outliers, and is incapable of capturing mobility organised around multiple centres. We propose a natural generalisation of the radius of gyration to a polycentric setting, as well as a novel metric to assess the quality of its description. With these notions, we propose a method to identify the centres in an individual's mobility and apply it to two large mobility datasets with socio-demographic features, showing that a polycentric description can capture features that a monocentric model is incapable of.

References in corpus (11)

• Modeling the scaling properties of human mobility
• Human Mobility: Models and Applications
• Geo-located Twitter as the proxy for global mobility patterns
• Understanding Human Mobility from Twitter
• Measuring large-scale social networks with high resolution
• Inferring transportation modes from GPS trajectories using a convolutional neural network
• Quantifying Human Mobility Perturbation and Resilience in Natural Disasters
• Modeling the polycentric transition of cities
• Estimating the number of communities in a network
• Mesoscopic structure and social aspects of human mobility
• Infostop: Scalable stop-location detection in multi-user mobility data