Identifying the hidden organizational principles and relevant structures of complex networks is fundamental to understand their properties. To this end, uncovering the structures involving the prominent nodes in a network is an effective approach. In temporal networks, the simultaneity of connections is crucial for temporally stable structures to arise. Here, we propose a measure to quantitatively investigate the tendency of well-connected nodes to form simultaneous and stable structures in a temporal network. We refer to this tendency as the temporal rich club phenomenon, characterized by a coefficient defined as the maximal value of the density of links between nodes with a minimal required degree, which remain stable for a certain duration. We illustrate the use of this concept by analysing diverse data sets and their temporal properties, from the role of cohesive structures in relation to processes unfolding on top of the network to the study of specific moments of interest in the evolution of the network.

识别复杂网络的隐藏组织原则和相关结构是理解其属性的基础。为此，揭示涉及网络中突出节点的结构是一种有效的方法。在时间网络中，连接的同时性对于时间稳定结构的出现至关重要。在这里，我们提出了一种方法来定量研究连接良好的节点在时间网络中形成同时且稳定的结构的趋势。我们将这种趋势称为时间丰富的俱乐部现象，其特征是一个系数定义为具有最小所需度的节点之间的链接密度的最大值，在一定时间内保持稳定。我们通过分析不同的数据集及其时间属性来说明这个概念的使用，