A sentiment analysis model to evaluate people’s opinion about artificial intelligence

Detalhes bibliográficos
Autor(a) principal: Buzaglo, Maria Nápoles Sarmento
Data de Publicação: 2020
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/93011
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
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spelling A sentiment analysis model to evaluate people’s opinion about artificial intelligenceSentiment AnalysisArtificial IntelligenceAINatural Language ProcessingNLPMachine LearningBinary ClassificationOpinion MiningDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsWith the use of internet, people are much more able to express and share what they think about a certain topic, their ideas and so on. Facebook and Twitter social networks, YouTube, online review sites like Zomato, online news sites or personal blogs are platforms that are usually used for this purpose. Every business wants to know what people think about their products; many people and politicians want to know the prediction for political elections; sometimes it can be useful to understand how opinions are distributed in some controversial themes. Thus, the analysis of textual data is also a need to stay competitive. In this work, through Sentiment Analysis techniques, different opinions from different online sources regarding to artificial intelligence are analyzed - a controversial field that have been a target of some debate in recent years. First, it is done a careful revision of the concept of Sentiment Analysis and all the involved techniques and processes such as data preprocessing, feature extraction and selection, sentiment classification approaches and machine learning algorithms – Naïve Bayes, Neural Networks, Random Forest, Support Vector Machine, Logistic Regression, Stochastic Gradient Descent. Based on previous works, the main conclusions, regarding to which techniques work better in which situations, are highlighted. Then, it is described the followed methodology in the application of Sentiment Analysis to artificial intelligence as a controversial field. The auxiliary tool used for this work is Python. In the end, results are presented and discussed.Castelli, MauroVanneschi, LeonardoRUNBuzaglo, Maria Nápoles Sarmento2020-02-19T18:16:35Z2020-01-232020-01-23T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/93011TID:202446000enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-10T15:52:46ZPortal AgregadorONG
dc.title.none.fl_str_mv A sentiment analysis model to evaluate people’s opinion about artificial intelligence
title A sentiment analysis model to evaluate people’s opinion about artificial intelligence
spellingShingle A sentiment analysis model to evaluate people’s opinion about artificial intelligence
Buzaglo, Maria Nápoles Sarmento
Sentiment Analysis
Artificial Intelligence
AI
Natural Language Processing
NLP
Machine Learning
Binary Classification
Opinion Mining
title_short A sentiment analysis model to evaluate people’s opinion about artificial intelligence
title_full A sentiment analysis model to evaluate people’s opinion about artificial intelligence
title_fullStr A sentiment analysis model to evaluate people’s opinion about artificial intelligence
title_full_unstemmed A sentiment analysis model to evaluate people’s opinion about artificial intelligence
title_sort A sentiment analysis model to evaluate people’s opinion about artificial intelligence
author Buzaglo, Maria Nápoles Sarmento
author_facet Buzaglo, Maria Nápoles Sarmento
author_role author
dc.contributor.none.fl_str_mv Castelli, Mauro
Vanneschi, Leonardo
RUN
dc.contributor.author.fl_str_mv Buzaglo, Maria Nápoles Sarmento
dc.subject.por.fl_str_mv Sentiment Analysis
Artificial Intelligence
AI
Natural Language Processing
NLP
Machine Learning
Binary Classification
Opinion Mining
topic Sentiment Analysis
Artificial Intelligence
AI
Natural Language Processing
NLP
Machine Learning
Binary Classification
Opinion Mining
description Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
publishDate 2020
dc.date.none.fl_str_mv 2020-02-19T18:16:35Z
2020-01-23
2020-01-23T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/93011
TID:202446000
url http://hdl.handle.net/10362/93011
identifier_str_mv TID:202446000
dc.language.iso.fl_str_mv eng
language eng
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eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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