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Resolution of ranking hierarchies in directed networks

Letizia, E; Barucca, P; Lillo, F; (2018) Resolution of ranking hierarchies in directed networks. PLoS One , 13 (2) , Article e0191604. 10.1371/journal.pone.0191604. Green open access

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Abstract

Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit.

Type: Article
Title: Resolution of ranking hierarchies in directed networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pone.0191604
Publisher version: http://doi.org/10.1371/journal.pone.0191604
Language: English
Additional information: Copyright: © 2018 Letizia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10045859
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