论文标题
结构重要性和进化：金融交易网络的应用
Structural importance and evolution: an application to financial transaction networks
论文作者
论文摘要
网络研究中的一个基本问题是识别重要节点。这通常是使用中心度指标来实现的，该指标将节点从其在网络中的位置进行排名。这种方法适用于不会随时间变化但不考虑网络的动态的静态网络。在这里，我们建议根据节点的重要性来衡量其强度的变化会影响网络的全局结构的重要性，我们根据其邻接矩阵的频谱进行衡量。我们将方法应用于股权交易网络中重要节点的识别，我们表明，尽管它仍然可以从静态网络进行计算，但我们的度量是随后交易的节点的良好预测指标。这意味着时间网络的静态表示可以包含有关其动态的信息。
A fundamental problem in the study of networks is the identification of important nodes. This is typically achieved using centrality metrics, which rank nodes in terms of their position in the network. This approach works well for static networks, that do not change over time, but does not consider the dynamics of the network. Here we propose instead to measure the importance of a node based on how much a change to its strength will impact the global structure of the network, which we measure in terms of the spectrum of its adjacency matrix. We apply our method to the identification of important nodes in equity transaction networks, and we show that, while it can still be computed from a static network, our measure is a good predictor of nodes subsequently transacting. This implies that static representations of temporal networks can contain information about their dynamics.
