Human Mobility and Predictability enriched by Social Phenomena Information

Abstract

The massive amounts of geolocation data collected from mobile phone records has sparked an ongoing effort to understand and predict the mobility patterns of human beings. In this work, we study the extent to which social phenomena are reflected in mobile phone data, focusing in particular in the cases of urban commute and major sports events. We illustrate how these events are reflected in the data, and show how information about the events can be used to improve predictability in a simple model for a mobile phone user's location.

References in corpus (3)

• Fast unfolding of communities in large networks
• Understanding individual human mobility patterns
• Exploring the Mobility of Mobile Phone Users

Cited by in corpus (4)

• A Study of Age and Gender seen through Mobile Phone Usage Patterns in Mexico
• A Bayesian Approach to Income Inference in a Communication Network
• Inference of Demographic Attributes based on Mobile Phone Usage Patterns and Social Network Topology
• Harnessing Mobile Phone Social Network Topology to Infer Users Demographic Attributes