Identification of Authoritative Nodes and Dismantling of Illicit Networks Using a Novel Metric for Measuring Strength of a Graph
Kartikeya Kansal, Arunabha Sen

TL;DR
This paper introduces a new network strength metric combining structural analysis and human perception, improving the identification of key nodes for dismantling illicit networks.
Contribution
The paper proposes a novel metric that integrates structural properties and human perception, validated through surveys, to better identify authoritative nodes in networks.
Findings
The new metric aligns more closely with human judgment.
It outperforms traditional metrics in identifying authoritative nodes.
It effectively dismantles both synthetic and real-world networks.
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Network Analysis Techniques · Graph theory and applications
