标题： 使用一种新的图强度测量度量来识别权威节点和破坏非法网络 显示英文标题

标题： Identification of Authoritative Nodes and Dismantling of Illicit Networks Using a Novel Metric for Measuring Strength of a Graph

摘要： 通过节点移除来瓦解犯罪网络、遏制流行病或虚假信息是一个被广泛研究的问题。 为了评估此类努力的效果，必须在移除节点前后测量网络的强度。 如果通过P1移除k个节点后的残余网络的强度小于通过P2移除后的强度，则认为过程P1比P2更有效。 这引出了核心问题：应该如何测量网络强度？ 现有的度量方法仅依赖于图的结构属性，例如连通性。 然而，在现实场景中，尤其是在执法领域，代理对网络强度的感知可能与结构评估有显著差异。 这些感知在传统度量中通常被忽视。 我们提出了一种新的强度度量方法，结合了结构属性和人类感知。 通过人类受试者调查，我们对现有度量方法验证了我们的方法。 我们的度量不仅更符合人类判断，而且在识别权威节点以及有效瓦解合成和现实世界网络方面优于传统方法。 显示英文摘要

摘要： Dismantling criminal networks or containing epidemics or misinformation through node removal is a well-studied problem. To evaluate the effectiveness of such efforts, one must measure the strength of the network before and after node removal. Process P1 is considered more effective than P2 if the strength of the residual network after removing k nodes via P1 is smaller than that from P2. This leads to the central question: How should network strength be measured? Existing metrics rely solely on structural properties of the graph, such as connectivity. However, in real-world scenarios, particularly in law enforcement, the perception of agents regarding network strength can differ significantly from structural assessments. These perceptions are often ignored in traditional metrics. We propose a new strength metric that integrates both structural properties and human perception. Using human subject surveys, we validate our approach against existing metrics. Our metric not only aligns more closely with human judgment but also outperforms traditional methods in identifying authoritative nodes and effectively dismantling both synthetic and real-world networks.