Latent space models for multiview network data

DC FieldValueLanguage
dc.contributor.authorSalter-Townshend, Michael-
dc.contributor.authorMcCormick, Tyler H.-
dc.date.accessioned2018-04-17T12:23:06Z-
dc.date.available2018-04-17T12:23:06Z-
dc.date.issued2017-09-
dc.identifier.citationAnnals of Applied Statisticsen
dc.identifier.issn1941-7330-
dc.identifier.urihttp://hdl.handle.net/10197/9338-
dc.description.abstractSocial relationships consist of interactions along multiple dimensions. In social networks, this means that individuals form multiple types of relationships with the same person (an individual will not trust all of his/her acquaintances, for example). Statistical models for these data require understanding two related types of dependence structure: (i) structure within each relationship type, or network view, and (ii) the association between views. In this paper we propose a statistical framework that parsimoniously represents dependence between relationship types while also maintaining enough flexibility to allow individuals to serve different roles in different relationship types. Our approach builds on work on latent space models for networks (see Hoff et al. (2002), for example). These models represent the propensity for two individuals to form edges as conditionally independent given the distance between the individuals in an unobserved social space. Our work departs from previous work in this area by representing dependence structure between network views through a Multivariate Bernoulli likelihood, providing a representation of between-view association. This approach infers correlations between views not explained by the latent space model. Using our method, we explore 6 multiview network structures across 75 villages in rural southern Karnataka, India (Banerjee et al., 2013).en
dc.language.isoenen
dc.publisherInstitute of Mathematical Studiesen
dc.subjectLatent space modelen
dc.subjectMultiview relational dataen
dc.subjectSocial networken
dc.titleLatent space models for multiview network dataen
dc.typeJournal Articleen
dc.internal.authorcontactothermichael.salter-townshend@ucd.ie-
dc.statusPeer revieweden
dc.identifier.volume11en
dc.identifier.issue3en
dc.identifier.startpage1217en
dc.identifier.endpage1244en
dc.identifier.doi10.1214/16-AOAS955-
dc.neeo.contributorSalter-Townshend|Michael|aut|-
dc.neeo.contributorMcCormick|Tyler H.|aut|-
dc.internal.rmsid801880938-
dc.date.updated2017-09-06T13:18:43Z-
dc.rights.licensehttps://creativecommons.org/licenses/by-nc-nd/3.0/ie/en
item.grantfulltextopen-
item.fulltextWith Fulltext-
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