Bartolucci, Silvia;
Caccioli, Fabio;
Caravelli, Francesco;
Vivo, Pierpaolo;
(2023)
Ranking influential nodes in networks from aggregate local information.
Physical Review Research
, 5
(3)
, Article 033123. 10.1103/PhysRevResearch.5.033123.
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Abstract
Many complex systems exhibit a natural hierarchy in which elements can be ranked according to a notion of “influence”. While the complete and accurate knowledge of the interactions between constituents is ordinarily required for the computation of nodes' influence, using a low-rank approximation we show that—in a variety of contexts—local and aggregate information about the neighborhoods of nodes is enough to reliably estimate how influential they are without the need to infer or reconstruct the whole map of interactions. Our framework is successful in approximating with high accuracy different incarnations of influence in systems as diverse as the WWW PageRank, trophic levels of ecosystems, upstreamness of industrial sectors in complex economies, and centrality measures of social networks, as long as the underlying network is not exceedingly sparse. We also discuss the implications of this “emerging locality” on the approximate calculation of nonlinear network observables.
| Type: | Article |
|---|---|
| Title: | Ranking influential nodes in networks from aggregate local information |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1103/PhysRevResearch.5.033123 |
| Publisher version: | https://doi.org/10.1103/PhysRevResearch.5.033123 |
| Language: | English |
| Additional information: | Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license, https://creativecommons.org/licenses/by-nc-nd/4.0/. |
| UCL classification: | UCL 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/10176938 |
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