  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.
