Modeling the Scaling Properties of Human Mobility in Virtual Space

Abstract People are increasingly involved in online activities. Online activities can be regarded as movements in virtual space, such as jumping from webpage to webpage while surfing online, switching channels while watching TV, and browsing commodities while shopping online, which can affect information propagation, innovation spread, social activities, etc. Most previous efforts have been devoted to modeling the scaling properties of human mobility in physical space. Few studies aim to establish a unified and integral model to understand the fundamental dynamics underlying human virtual mobility. In this paper, we study human mobility in virtual space empirically and theoretically based on two datasets involving TV watching and online shopping and attempt to answer three unsolved issues. First, human virtual mobility shares common features, supported by the fact that striking agreements appear in the scaling properties of both datasets. Second, there exists a universal rule governing an individual's choice in virtual mobility, which is distinct from that in the real world due to travel restrictions. Third, there exists a unified model incorporating the behavior rule unique to virtual space under the framework of Exploration and Preferential Return, which can be used to reproduce the scaling properties of virtual mobility. We reveal the mechanism behind human virtual mobility through consistent scaling properties and develop a corresponding dynamic model based on empirical data.