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dc.contributor.authorMorales Arévalo, Juan Carlos
dc.contributor.authorDenegri Coria, Marianela
dc.contributor.authorHilario Rivas, Jorge Luis
dc.contributor.authorHilario Cárdenas, Jorge Rubén
dc.contributor.authorPrado Juscamaita, Justina Isabel
dc.date.accessioned2021-11-10T21:44:25Z
dc.date.available2021-11-10T21:44:25Z
dc.date.issued2021
dc.identifier.issn1309-4653
dc.identifier.urihttps://hdl.handle.net/20.500.12867/4571
dc.description.abstractSentiment analysis is used to analyse customer sentiment by the process of using natural language processing, text analysis, and statistics. A good customer survey understands the sentiment of their customers—what, how and why they’re saying it. Sentiment dataset can be found mainly in tweets, comments and reviews. Sentiment Analysis understands emotions with the help of software, and it is playing an inevitable role in today’s workplaces. Sentiment analysis for opinion mining has become an emerging area where more research and innovations are done. Sentiment or opinion analysis based on a domain is done using several algorithms. Machine learning is a concept among this area. In this, the main focus is on the supervised sentiment analysis or opinion mining algorithms. Supervised learning is a division coming under machine learning. Different methods of supervised learning and sentiment analysis algorithms are considered and their mode of functioning is studied. Main focus of this paper is on the recent trends of research and studies for sentiment classification, taking into consideration the accuracy of different algorithmic techniques that can be implemented for accurate prediction in sentiment Analysises_PE
dc.formatapplication/pdfes_PE
dc.language.isospaes_PE
dc.publisherKaradeniz Technical Universityes_PE
dc.relation.ispartofseriesKaradeniz Technical University;vol. 12, n° 14 (2021), pp. 2000 - 2012
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/es_PE
dc.sourceRepositorio Institucional - UTPes_PE
dc.sourceUniversidad Tecnológica del Perúes_PE
dc.subjectOpinion mining (análisis de sentimientos)es_PE
dc.subjectMachine learninges_PE
dc.subjectSupervised learninges_PE
dc.subjectAprendizaje supervisadoes_PE
dc.subjectAprendizaje atomáticoes_PE
dc.titleSupervised Sentiment Analysis Algorithmses_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.journalTurkish Journal of Computer and Mathematics Educationes_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#5.02.04es_PE
dc.description.sedeCampus Lima Centroes_PE
dc.publisher.countryTRes_PE
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_PE


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