2024/11/29 by Francesca Arrigo, Arrigo, Francesca, Daniele Bertaccini +3
Computer Science · #05C50 #05C90 #65F99 #68R10 #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #FOS: Mathematics #Numerical Analysis (math.NA) #Social and Information Networks (cs.SI)
paper · doi:10.48550/arxiv.2411.19560
openalex publication_date 2024/11/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We develop efficient and effective strategies for the update of Katz centralities after node and edge removal in simple graphs. We provide explicit formulas for the ``loss of walks" a network suffers when nodes/edges are removed, and use these to inform our algorithms. The theory builds on the newly introduced concept of \cF-avoiding first-passage walks. Further, bounds on the change of total network communicability are also derived. Extensive numerical experiments on synthetic and real-world networks complement our theoretical results.