Pan Raj Kumar, Saramäki Jari
BECS, School of Science and Technology, Aalto University, Finland.
Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Jul;84(1 Pt 2):016105. doi: 10.1103/PhysRevE.84.016105. Epub 2011 Jul 18.
In temporal networks, where nodes interact via sequences of temporary events, information or resources can only flow through paths that follow the time ordering of events. Such temporal paths play a crucial role in dynamic processes. However, since networks have so far been usually considered static or quasistatic, the properties of temporal paths are not yet well understood. Building on a definition and algorithmic implementation of the average temporal distance between nodes, we study temporal paths in empirical networks of human communication and air transport. Although temporal distances correlate with static graph distances, there is a large spread, and nodes that appear close from the static network view may be connected via slow paths or not at all. Differences between static and temporal properties are further highlighted in studies of the temporal closeness centrality. In addition, correlations and heterogeneities in the underlying event sequences affect temporal path lengths, increasing temporal distances in communication networks and decreasing them in the air transport network.
在时间网络中，节点通过一系列临时事件进行交互，信息或资源只能沿着遵循事件时间顺序的路径流动。这种时间路径在动态过程中起着至关重要的作用。然而，由于到目前为止网络通常被视为静态或准静态的，时间路径的特性尚未得到很好的理解。基于节点之间平均时间距离的定义和算法实现，我们研究了人类通信和航空运输的实证网络中的时间路径。尽管时间距离与静态图距离相关，但存在很大差异，并且从静态网络角度看似接近的节点可能通过缓慢路径连接，或者根本不连接。在时间接近中心性的研究中，静态和时间属性之间的差异进一步凸显。此外，底层事件序列中的相关性和异质性会影响时间路径长度，增加通信网络中的时间距离，而在航空运输网络中则会减小时间距离。
