论文标题
影响力和影响力：导向复杂网络的全球方向性
Influence and Influenceability: Global Directionality in Directed Complex Networks
论文作者
论文摘要
知道哪些节点在复杂的网络中具有影响力，以及网络是否可以受到一小部分节点的影响是网络分析的关键部分。但是，许多传统的重要性措施集中在节点级别信息上，而无需考虑全球网络体系结构。我们使用营养分析的方法来研究定向网络，并表明有指示网络中的“影响”和“影响力”都取决于分层结构和全球方向性，分别通过营养水平和营养相干性衡量。我们表明，在有指导的网络中，营养层次结构可以解释：可以到达大多数其他的节点；特征向量中心位置的位置；在观点或振荡器动力学中塑造行为的态度；以及哪些策略将在广义岩纸剪辑游戏中取得成功。此外，我们表明这些现象是由全球方向性介导的。我们还强调了与影响力相关的真实网络的其他结构特性，例如伪造的，它取决于营养相干性。这些结果适用于任何有针对性的网络和突出的原则，该节点层次结构对于理解由全球方向性介导的网络影响至关重要，适用于许多现实世界动态。
Knowing which nodes are influential in a complex network and whether the network can be influenced by a small subset of nodes is a key part of network analysis. However, many traditional measures of importance focus on node level information without considering the global network architecture. We use the method of Trophic Analysis to study directed networks and show that both "influence" and "influenceability" in directed networks depend on the hierarchical structure and the global directionality, as measured by the trophic levels and trophic coherence, respectively. We show that in directed networks trophic hierarchy can explain: the nodes that can reach the most others; where the eigenvector centrality localises; which nodes shape the behaviour in opinion or oscillator dynamics; and which strategies will be successful in generalised rock-paper-scissors games. We show, moreover, that these phenomena are mediated by the global directionality. We also highlight other structural properties of real networks related to influenceability, such as the pseudospectra, which depend on trophic coherence. These results apply to any directed network and the principles highlighted, that node hierarchy is essential for understanding network influence, mediated by global directionality, are applicable to many real-world dynamics.
