时变网络中相互作用持续性的刻画
Characterization of interactions' persistence in time-varying networks
摘要：
许多复杂的网络系统在其顶点之间表现出易变的动态相互作用，其顺序和持久性对发生在其上的动态过程的结果产生影响。为了量化和表征时变网络快照的相似性-持久性的代理，-我们提出了一个研究的持久性的相互作用的基础上的描述符命名为\emph{temporality}。我们使用时间性的平均值$\overline{\mathcal{T}}$来评估"\emph{special}"在有序快照序列的配置空间内是如何给定时变网络的。我们分析了几个经验网络的时间性，发现经验序列比随机序列更相似。我们还研究了相互作用发生时的（时间）分辨率对$\overline{\mathcal{T}}$的影响。
英文摘要：
Many complex networked systems exhibit volatile dynamic interactions among their vertices, whose order and persistence reverberate on the outcome of dynamical processes taking place on them. To quantify and characterize the similarity of the snapshots of a time-varying network -- a proxy for the persistence,-- we present a study on the persistence of the interactions based on a descriptor named \emph{temporality}. We use the average value of the temporality, $\overline{\mathcal{T}}$, to assess how ``\emph{special}'' is a given time-varying network within the configuration space of ordered sequences of snapshots. We analyze the temporality of several empirical networks and find that empirical sequences are much more similar than their randomized counterparts. We study also the effects on $\overline{\mathcal{T}}$ induced by the (time) resolution at which interactions take place.
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