EXplainable Artificial Intelligence in sentiment analysis of posts about Covid-19 vaccination on Twitter

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorFeitosa, Juliana Da Costa-
Autor(es): dc.creatorDe Camargo, Luiz Felipe-
Autor(es): dc.creatorBonatti, Eloisa-
Autor(es): dc.creatorSimioni, Giovanna-
Autor(es): dc.creatorBrega, José Remo Ferreira-
Data de aceite: dc.date.accessioned2025-08-21T15:53:10Z-
Data de disponibilização: dc.date.available2025-08-21T15:53:10Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-10-22-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1145/3617023.3617033-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/309605-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/309605-
Descrição: dc.descriptionConsidering the impact of the use of Artificial Intelligence (AI) in the most diverse branches of society and the use of eXplicable Artificial Intelligence (XAI) to improve the interpretability of these intelligent models, this paper aims to analyze some existing XAI methods to verify their effectiveness. To this end, experiments were conducted with LIME, SHAP, and Eli5 solutions in a scenario of sentiment classifications in Twitter posts about the Covid-19 vaccination process in Brazil. Thus, it is observed that the tools provide relevant information about the aspects that interfere in the classification of tweets as favorable or not favorable to vaccination, which allows concluding that the methods bring the necessary transparency to confirm the AI decisions regarding the sentiments related to the vaccination process in Brazil.-
Descrição: dc.descriptionSao Paulo State University Department of Computing-
Descrição: dc.descriptionSao Paulo State University Department of Computing-
Formato: dc.format65-72-
Idioma: dc.languagept_BR-
Relação: dc.relationACM International Conference Proceeding Series-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectCOVID-19-
Palavras-chave: dc.subjectexplainability-
Palavras-chave: dc.subjectexplicable artificial intelligence-
Palavras-chave: dc.subjectsentiment analysis-
Título: dc.titleEXplainable Artificial Intelligence in sentiment analysis of posts about Covid-19 vaccination on Twitter-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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