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Trends and topics in geographically weighted regression research from 1996 to 2019

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dc.contributor.authorDe La Hoz-M, Javier
dc.contributor.authorFernandez-Gómez, María José
dc.contributor.authorMendes, Susana
dc.date.accessioned2022-08-01T15:33:30Z
dc.date.available2022-08-01T15:33:30Z
dc.date.issued2021
dc.description.abstractThis research was conducted in order to improve the understanding of the structure, contents, and trend of topics within the existing literature in the field of geographically weighted regression. Additionally, it intended to determine and produce a mapping of scientific networks in the domain of geographically weighted regression. The proposed methodology implements a combination of bibliometric techniques and modelling of topics in order to extract the latent topics from the collected literature by utilising latent Dirichlet allocation and a machine learning tool. The results identified the most prolific authors, the most cited authors, the most representative articles and journals, and the countries which are responsible for the publications.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationDe La Hoz, J., Fernandez-Gómez, M.J. & Mendes, S. (2021) Trends and topics in geographically weighted regression research from 1996 to 2019. Area, 54(1), 105–117. https://doi.org/10.1111/area.12757pt_PT
dc.identifier.doi10.1111/area.12757pt_PT
dc.identifier.issn0004-0894
dc.identifier.urihttp://hdl.handle.net/10400.8/7476
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherWileypt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectBibliometric analysispt_PT
dc.subjectCollaboration patternpt_PT
dc.subjectGeographically weighted regressionpt_PT
dc.subjectLatent Dirichlet allocationpt_PT
dc.subjectMachine learningpt_PT
dc.subjectTopic modellingpt_PT
dc.titleTrends and topics in geographically weighted regression research from 1996 to 2019pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage117pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage105pt_PT
oaire.citation.titleAreapt_PT
oaire.citation.volume54pt_PT
person.familyNameDE LA HOZ-M
person.familyNameMendes
person.givenNameJAVIER
person.givenNameSusana
person.identifier322266
person.identifier.ciencia-id4514-12E2-1FD9
person.identifier.orcid0000-0001-7779-0803
person.identifier.orcid0000-0001-9681-3169
person.identifier.scopus-author-id34976470100
person.identifier.scopus-author-id33568138000
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication4c86a446-22da-425a-99d0-fd90e7e184ad
relation.isAuthorOfPublicationdb5be03b-2077-482b-a9cf-8b3e84861276
relation.isAuthorOfPublication.latestForDiscovery4c86a446-22da-425a-99d0-fd90e7e184ad

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