Departament de Física Fonamental, Universitat de Barcelona, Martí i Franquès 1, 08028, Barcelona, Spain.
Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, Barcelona, Spain.
Sci Rep. 2017 Aug 17;7(1):8597. doi: 10.1038/s41598-017-07591-0.
Multi-layered networks represent a major advance in the description of natural complex systems, and their study has shed light on new physical phenomena. Despite its importance, however, the role of the temporal dimension in their structure and function has not been investigated in much detail so far. Here we study the temporal correlations between layers exhibited by real social multiplex networks. At a basic level, the presence of such correlations implies a certain degree of predictability in the contact pattern, as we quantify by an extension of the entropy and mutual information analyses proposed for the single-layer case. At a different level, we demonstrate that temporal correlations are a signature of a 'multitasking' behavior of network agents, characterized by a higher level of switching between different social activities than expected in a uncorrelated pattern. Moreover, temporal correlations significantly affect the dynamics of coupled epidemic processes unfolding on the network. Our work opens the way for the systematic study of temporal multiplex networks and we anticipate it will be of interest to researchers in a broad array of fields.
多层网络代表了对自然复杂系统描述的重大进展,其研究揭示了新的物理现象。然而,尽管它很重要,但迄今为止,其结构和功能中的时间维度的作用还没有被详细研究。在这里,我们研究了真实社会多重网络中表现出的层间时间相关性。在基本层面上,这种相关性的存在意味着在接触模式中存在一定程度的可预测性,我们通过对单一层情况提出的熵和互信息分析的扩展来量化这种可预测性。在不同的层面上,我们证明了时间相关性是网络代理“多任务”行为的特征,其表现为在不同的社会活动之间切换的水平高于无相关性模式下的预期,这是一种更高层次的切换。此外,时间相关性会显著影响网络上展开的耦合传染病过程的动态。我们的工作为系统研究时间多重网络开辟了道路,我们预计它将引起广泛领域的研究人员的兴趣。