This paper provides an analysis of human mobility data in an urban area using the amount of available bikes in the stations of the community bicycle program Bicing in Barcelona. Based on data sampled from the operator’s website, it is possible to detect temporal and geographic mobility patterns within the city. These patterns are applied to predict the number of available bikes for any station ...

Theories based on partial equilibrium reasoning alone cannot explain the widespread negative cross-sectional correlation between parental wages and fertility, without restrictive assumptions on preferences and childcare costs. We argue that incorporating a dynamic general equilibrium analysis of returns to human capital can help explain observed empirical patterns. Other by-products of this the...

Taxi trajectories reflect human mobility over the urban roads’ network. Although taxi drivers cruise the same city streets, there is an observed variation in their daily profit. To reveal the reasons behind this issue, this study introduces a novel approach for investigating and understanding the impact of human mobility patterns (taxi drivers’ behavior) on daily drivers’ profit. Firstly, a K-m...

Abstract. Understanding urban mobility is a fundamental question for institutional organizations (transport authorities, city halls) and it involves many different fields like social sciences, urbanism or geography. With the increasing number of probes tracking human locations, like magnetic pass for urban transportation, road sensors, CCTV systems or cell phones, mobility data are exponentiall...

We quantify and derive a general model for the collaboration stability of human mobility demonstrate its importance networking applications. Our results that opportunities are highly dependent on context where they take place, with diurnal patterns spatial characteristics being particularly important.

Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Using the concept of motifs from network theory, w...

We present and test a sequential learning algorithm for the short-term prediction of human mobility. This novel approach pairs the Exponential Weights forecaster with a very large ensemble of experts. The experts are individual sequence prediction algorithms constructed from the mobility traces of 10 million roaming mobile phone users in a European country. Average prediction accuracy is signif...