dc.contributor.author | Lacasa, L | |
dc.contributor.author | Stramaglia, S | |
dc.contributor.author | Marinazzo, D | |
dc.date.accessioned | 2021-06-09T12:58:03Z | |
dc.date.available | 2021-06-09T12:58:03Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/72437 | |
dc.description.abstract | Network similarity measures quantify how and when two networks are symmetrically related, including measures of statistical association such as pairwise distance or other correlation measures between networks or between the layers of a multiplex network, but neither can directly unveil whether there are hidden confounding network factors nor can they estimate when such correlation is underpinned by a causal relation. In this work we extend this pairwise conceptual framework to triplets of networks and quantify how and when a network is related to a second network directly or via the indirect mediation or interaction with a third network. Accordingly, we develop a simple and intuitive set-theoretic approach to quantify mediation and suppression between networks. We validate our theory with synthetic models and further apply it to triplets of real-world networks, unveiling mediation and suppression effects which emerge when considering different modes of interaction in online social networks and different routes of information processing in the brain. | en_US |
dc.rights | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. | |
dc.subject | cs.SI | en_US |
dc.subject | cs.SI | en_US |
dc.subject | physics.data-an | en_US |
dc.subject | physics.soc-ph | en_US |
dc.title | Beyond pairwise network similarity: exploring Mediation and Suppression between networks | en_US |
dc.type | Article | en_US |
dc.rights.holder | © 2021, The Author(s) | |
pubs.author-url | http://arxiv.org/abs/2012.09006v1 | en_US |
pubs.notes | Not known | en_US |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |
qmul.funder | Early career fellowship: SIG-NET::Engineering and Physical Sciences Research Council | en_US |