Recognizing Distance-Count Matrices is Difficult
Social and Information Networks
2025-11-25 v2
Abstract
Axiomatization of centrality measures often involves proving that something cannot hold by providing a counterexample (i.e., a graph for which that specific centrality index fails to have a given property). In the context of geometric centralities, building such counterexamples requires constructing a graph with specific distance counts between nodes, as expressed by its distance-count matrix. We prove that deciding whether a matrix is the distance-count matrix of a graph is strongly NP-complete. This negative result implies that a brute-force approach to building this kind of counterexample is out of question, and cleverer approaches are required.
Cite
@article{arxiv.2508.18857,
title = {Recognizing Distance-Count Matrices is Difficult},
author = {Paolo Boldi and Flavio Furia and Chiara Prezioso and Ian Stewart},
journal= {arXiv preprint arXiv:2508.18857},
year = {2025}
}