Optimizing Natural Language Processing Applications for Sentiment Analysis

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorLopes, Anderson Claiton-
Autor(es): dc.creatorGomes, Vitoria Zanon-
Autor(es): dc.creatorZafalon, Geraldo Francisco Donegá-
Data de aceite: dc.date.accessioned2025-08-21T23:12:30Z-
Data de disponibilização: dc.date.available2025-08-21T23:12:30Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5220/0012632000003690-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/302171-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/302171-
Descrição: dc.descriptionRecent technological advances have stimulated the exponential growth of social network data, driving an increase in research into sentiment analysis. Thus, studies exploring the intersection of Natural Language Processing and social network analysis are playing an important role, specially those one focused on heuristic approaches and the integration of algorithms with machine learning. This work centers on the application of sentiment analysis techniques, employing algorithms such as Logistic Regression and Support Vector Machines. The analyses were performed on datasets comprising 5,000 and 10,000 tweets, and our findings reveal the efficient performance of Logistic Regression in comparison with other approach. Logistc Regression improved the performed in almost all measures, with emphasis to accuracy, recall and F1-Score.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionDepartment of Computer Science and Statistics Universidade Estadual Paulista (UNESP), Rua Cristóvão Colombo, 2265, Jardim Nazareth, SP-
Descrição: dc.descriptionDepartment of Computer Science and Statistics Universidade Estadual Paulista (UNESP), Rua Cristóvão Colombo, 2265, Jardim Nazareth, SP-
Descrição: dc.descriptionFAPESP: 2020/08615-8-
Descrição: dc.descriptionCAPES: 88887.686064/2022-00-
Formato: dc.format698-705-
Idioma: dc.languageen-
Relação: dc.relationInternational Conference on Enterprise Information Systems, ICEIS - Proceedings-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectMachine Learning-
Palavras-chave: dc.subjectNatural Language Processing-
Palavras-chave: dc.subjectSentiment Analysis-
Título: dc.titleOptimizing Natural Language Processing Applications for Sentiment Analysis-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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