The recent availability of digital traces from information and communications technologies has facilitated the study of both individual- and population-level movement with unprecedented spatio-temporal resolution, enabling us to better understand a plethora of socio-economic processes such as urbanization, transportation, impact on the environment and epidemic spreading to name a few. Using empirical spatio-temporal trends, several mobility models have been proposed to explain the observed regularities in human movement. With the advent of the World Wide Web, a new type of virtual mobility has emerged that has begun to supplant many traditional facets of human activity. Here, we conduct a systematic analysis of physical and virtual movement, uncovering both similarities and differences in their statistical patterns. The differences manifest themselves primarily in the temporal regime, as a signature of the spatial and economic constraints inherent in physical movement, features that are predominantly absent in the virtual space. We demonstrate that once one moves to the time-independent space of events, i.e. the sequences of visited locations, these differences vanish, and the statistical patterns of physical and virtual mobility are identical. The observed similarity in navigating these markedly different domains points towards a common mechanism governing the movement patterns, a feature we describe through a Metropolis–Hastings type optimization model, where individuals navigate locations through decision-making processes resembling a cost–benefit analysis of the utility of locations. In contrast to existing phenomenological models of mobility, we show that our model can reproduce the commonalities in the empirically observed statistics with minimal input.

中文翻译：

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揭示物理和虚拟移动性之间的异同

最近来自信息和通信技术的数字痕迹的可用性以前所未有的时空分辨率促进了对个人和人口水平移动的研究，使我们能够更好地了解过多的社会经济过程，如城市化、交通、影响关于环境和流行病的传播等等。使用经验时空趋势，已经提出了几种移动模型来解释观察到的人类运动规律。随着万维网的出现，出现了一种新型的虚拟移动性，它开始取代人类活动的许多传统方面。在这里，我们对物理和虚拟运动进行了系统分析，揭示了它们统计模式的异同。这些差异主要表现在时​​间制度上，作为物理运动固有的空间和经济约束的标志，虚拟空间中主要不存在的特征。我们证明，一旦一个人移动到事件的时间无关空间，即访问位置的序列，这些差异就会消失，并且物理和虚拟移动的统计模式是相同的。在导航这些明显不同的领域时观察到的相似性指向一个共同的机制来控制运动模式，这是我们通过 Metropolis-Hastings 类型优化模型描述的一个特征，其中个人通过类似于效用成本效益分析的决策过程来导航位置的位置。与现有的流动现象学模型相比，