Latent space generative model for bipartite networks

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dc.contributor.author Vasques Filho, Demival en
dc.contributor.author O'Neale, Dion en
dc.date.accessioned 2020-04-08T22:24:55Z en
dc.date.issued 2019-10-28 en
dc.identifier.citation Arxiv (1910.12488v1). 28 Oct 2019. 14 pages en
dc.identifier.uri http://hdl.handle.net/2292/50290 en
dc.description.abstract Generative network models are extremely useful for understanding the mechanisms that operate in network formation and are widely used across several areas of knowledge. However, when it comes to bipartite networks -- a class of network frequently encountered in social systems -- generative models are practically non-existent. Here, we propose a latent space generative model for bipartite networks growing in a hyperbolic plan. It is an extension of a model previously proposed for one-mode networks, based on a maximum entropy approach. We show that, by reproducing bipartite structural properties, such as degree distributions and small cycles, bipartite networks can be better modelled and one-mode projected network properties can be naturally assessed. en
dc.relation.ispartof Arxiv en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri https://arxiv.org/licenses/nonexclusive-distrib/1.0/license.html en
dc.subject physics.soc-ph en
dc.subject physics.soc-ph en
dc.subject cond-mat.stat-mech en
dc.title Latent space generative model for bipartite networks en
dc.type Report en
dc.rights.holder Copyright: The authors en
pubs.author-url http://arxiv.org/abs/1910.12488v1 en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Working Paper en
pubs.elements-id 785109 en
pubs.org-id Science en
pubs.org-id Physics en
pubs.arxiv-id 1910.12488 en
pubs.number 1910.12488v1 en
pubs.record-created-at-source-date 2020-04-09 en


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