Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/25096
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Vicente, M. | - |
dc.contributor.author | Batista, F. | - |
dc.contributor.author | Carvalho, J. | - |
dc.contributor.editor | Adnan Yazici, Nikhil R. Pal, Uzat Kaymak | - |
dc.date.accessioned | 2022-04-08T09:09:34Z | - |
dc.date.available | 2022-04-08T09:09:34Z | - |
dc.date.issued | 2015 | - |
dc.identifier.isbn | 978-1-4673-7428-6 | - |
dc.identifier.issn | 1544-5615 | - |
dc.identifier.uri | http://hdl.handle.net/10071/25096 | - |
dc.description.abstract | This paper describes an approach to automatically detect the gender of Twitter users, based only on clues provided by their profile information in an unstructured form. A number of features that capture phenomena specific of Twitter users is proposed and evaluated on a dataset of about 242K English language users. Different supervised and unsupervised approaches are used to assess the performance of the proposed features, including Naive Bayes variants, Logistic Regression, Support Vector Machines, Fuzzy c-Means clustering, and K-means. An unsupervised approach based on Fuzzy c-Means proved to be very suitable for this task, returning the correct gender for about 96% of the users. | eng |
dc.language.iso | eng | - |
dc.publisher | IEEE | - |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FCEC%2F50021%2F2013/PT | - |
dc.rights | openAccess | - |
dc.subject | eng | |
dc.subject | Gender detection | eng |
dc.subject | Fuzzy c-means | eng |
dc.subject | Supervised and unsupervised methods | eng |
dc.title | Twitter gender classification using user unstructured information | eng |
dc.type | conferenceObject | - |
dc.event.type | Conferência | pt |
dc.event.location | Istambul | eng |
dc.event.date | 2015 | - |
dc.peerreviewed | yes | - |
dc.journal | IEEE International Fuzzy Systems conference proceedings | - |
degois.publication.location | Istambul | eng |
degois.publication.title | Twitter gender classification using user unstructured information | eng |
dc.date.updated | 2022-04-08T10:04:53Z | - |
dc.description.version | info:eu-repo/semantics/acceptedVersion | - |
dc.identifier.doi | 10.1109/FUZZ-IEEE.2015.7338102 | - |
dc.subject.fos | Domínio/Área Científica::Ciências Naturais::Ciências Físicas | por |
iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-24678 | - |
iscte.alternateIdentifiers.scopus | 2-s2.0-84975745653 | - |
Aparece nas coleções: | IT-CRI - Comunicações a conferências internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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conferenceobject_24678.pdf | Versão Aceite | 139,68 kB | Adobe PDF | Ver/Abrir |
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