Human mobility

Contrasting social and non-social sources of predictability in human mobility

In this paper, we apply entropy and predictability measures to analyse and bound the predictive information of an individual's mobility pattern and the flow of that information from their top social ties and from their non-social colocators.

Predictability states in human mobility

we propose that the predictability in human mobility is a state and not a static trait of individuals. First, we show that time (of the week) explains people’s whereabouts more than the sequences of locations they visit. Then, we show that not only does predictability depend on time but also the type of activity an individual is engaged in, thus establishing the importance of contexts in human mobility..

Identification of Human Mobility Modes using Socio-Spatio-Temporal Predictive Models

The scientific analysis of the regularities observed in individual and collective human movement trajectories is of fundamental relevance to a wide range of areas urban planning, the prevention of epidemics, and natural security issues such as detection of clandestine activity, to name but a few. The ubiquity of mobile phones and location-based social media has enabled the capture of comprehensive, time-resolved individual information, offering a unique opportunity to observe human activity on an unprecedented scale. Indeed, recent theoretical developments suggest that a perfect algorithm can predict a person's whereabouts with almost 90% certainty, given past observations of their location visits. Yet, major gaps remain in our understanding of human mobility dynamics.