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dc.contributor.authorViloria, Amelecspa
dc.contributor.authorParra Negrete, Kevinspa
dc.contributor.authorConde, Marcialspa
dc.contributor.authorPineda Lezama, Omar Bonergespa
dc.date.accessioned2021-02-19T16:51:59Z
dc.date.available2021-02-19T16:51:59Z
dc.date.issued2020-11-05
dc.identifier.urihttps://hdl.handle.net/11323/7881spa
dc.description.abstractThe use of social networks is steadily increasing worldwide. Hundreds of users daily register in the different existing platforms, therefore, the content extracted from the social networks is fundamental for tasks such as sentiment analysis, detection of author profiles, identification of authors, opinions mining, plagiarism detection, calculation of similarity between texts and to develop robust systems that help to make decisions in related areas such as politics, education, economy, among others. This paper provides a lexical aid for the pre-processing of texts posted in social networks evolved for the subsequent languages: English, Spanish, Dutch and Italian.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.publisherCorporación Universidad de la Costaspa
dc.relation.ispartofhttps://link.springer.com/bookseries/7899spa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.sourceCommunications in Computer and Information Sciencespa
dc.subjectAuthor profilesspa
dc.subjectInformation and communicationspa
dc.subjectSocial network lexiconspa
dc.subjectMachine learningspa
dc.titleCompilation of a social network lexicon for determining the profile of authorsspa
dc.typeArtículo de revistaspa
dc.source.urlhttps://link.springer.com/chapter/10.1007/978-981-15-9671-1_23spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1007/978-981-15-9671-1_23spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
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