Understanding mobility in a social petri dish

TL;DR

This study analyzes human mobility within a social online game, revealing that social and economic factors, along with spatial constraints, significantly influence movement patterns, which can be effectively modeled using community detection and memory effects.

Contribution

It provides a comprehensive analysis of mobility patterns in a complete social and economic context, highlighting the importance of socio-economic regions and memory in trajectory modeling.

Findings

Mobility is influenced by physical distances and socio-economic regions.

Community detection accurately identifies socio-economic areas from movement data.

Long-term memory is crucial for modeling individual trajectories.

Abstract

Despite the recent availability of large data sets on human movements, a full understanding of the rules governing motion within social systems is still missing, due to incomplete information on the socio-economic factors and to often limited spatio-temporal resolutions. Here we study an entire society of individuals, the players of an online-game, with complete information on their movements in a network-shaped universe and on their social and economic interactions. Such a "socio-economic laboratory" allows to unveil the intricate interplay of spatial constraints, social and economic factors, and patterns of mobility. We find that the motion of individuals is not only constrained by physical distances, but also strongly shaped by the presence of socio-economic areas. These regions can be recovered perfectly by community detection methods solely based on the measured human dynamics. Moreover, we uncover that long-term memory in the time-order of visited locations is the essential ingredient for modeling the trajectories.