On node ranking in graphs
Abstract
The ranking of nodes in a network according to their ``importance'' is a classic problem that has attracted the interest of different scientific communities in the last decades. The current COVID-19 pandemic has recently rejuvenated the interest in this problem, as it is related to the selection of which individuals should be tested in a population of asymptomatic individuals, or which individuals should be vaccinated first. Motivated by the COVID-19 spreading dynamics, in this paper we review the most popular methods for node ranking in undirected unweighted graphs, and compare their performance in a benchmark realistic network, that takes into account the community-based structure of society. Also, we generalize a classic benchmark network originally proposed by Newman for ranking nodes in unweighted graphs, to show how ranks change in the weighted case.
Cite
@article{arxiv.2107.09487,
title = {On node ranking in graphs},
author = {Ekaterina Dudkina and Michelangelo Bin and Jane Breen and Emanuele Crisostomi and Pietro Ferraro and Steve Kirkland and Jakub Marecek and Roderick Murray-Smith and Thomas Parisini and Lewi Stone and Serife Yilmaz and Robert Shorten},
journal= {arXiv preprint arXiv:2107.09487},
year = {2023}
}