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Thèse de Doctorat
DOI
10.11606/T.3.2016.tde-19072016-115713
Document
Auteur
Nom complet
Renata Lopes Rosa
Adresse Mail
Unité de l'USP
Domain de Connaissance
Date de Soutenance
Editeur
São Paulo, 2015
Directeur
Jury
Bressan, Graça (Président)
Goularte, Rudinei
Kovach, Stephan
Oliveira, José Maria Parente de
Ruggiero, Wilson Vicente
Titre en portugais
Análise de sentimentos e afetividade de textos extraídos das redes sociais.
Mots-clés en portugais
Análise de dados
Comunicação
Internet
Redes sociais
Resumé en portugais
Atualmente, os usuários expressam seus desejos e preferências em relação a um objeto, conteúdo ou evento por meio das redes sociais; portanto, analisar os sentimentos de uma pessoa no mundo digital sobre o que a rodeia tem sido cada vez mais frequente com o intuito de conhecer as preferências desta pessoa. O estudo propõe um novo mecanismo e cálculo de sentimentos e afetividade, aperfeiçoando a análise de sentimentos. Um mecanismo de cálculo de sentimentos associado a um fator de correção correspondente a n-gramas, tempos verbais, expressões e às características pessoas, tais como idade, gênero e escolaridade é desenvolvido neste trabalho. Os sentimentos negativos, neutros e positivos são extraídos de frases das redes sociais. As frases são classificadas em intensidade de sentimentos e em polaridade positiva, negativa ou neutra, por meio de um novo dicionário de palavras em português e de um novo cálculo de sentimentos. O cálculo de sentimentos possui regras específicas para tempos verbais (presente e passado) e advérbios. Os sentimentos das palavras são extraídos por meio de adjetivos, substantivos, palavras únicas (unigramas) e palavras que associadas (bigramas e trigramas) possuem um significado diferente de palavras únicas. Para validação do desempenho do dicionário e do novo mecanismo de cálculo de sentimentos, os resultados sao comparados com uma ferramenta de análise de sentimentos j´a existente, a SentiStrength e são validados por meio de testes subjetivos, com avaliadores remotos, com uma técnica denominada de crowdsourcing e por aprendizagem de máquina. O estudo também analisa a afetividade das frases e propõe uma métrica denominada de Brazillian Affective Metric (AFMBr), extraindo emoções de raiva, alegria, tristeza, surpresa e nojo. A solução de análise de sentimentos e afetividade é aplicada em um sistema de recomendação de músicas, como estudo de caso, o qual sugere conteúdos conforme o estado sentimental da pessoa.
Titre en anglais
Sentiment analysis and affection of texts extracted from social networks.
Mots-clés en anglais
Communication
Data analysis
Internet
Social networks
Resumé en anglais
Currently, users express their wishes and preferences in relation to an object, content or event through social networks; therefore analyze the sentiments of a person in the digital world about what surrounds the person has been increasingly used in order to know the preferences of this person. The study proposes new metrics of sentiments and affection, improving the sentiment analysis. The sentiment analysis metric associated with a corresponding correction factor for n-grams, tenses, expressions and personal characteristics such as age, gender and education is developed in this work. Negative, neutral and positive sentiments are extracted from social networks phrases. The sentences are ranked in positive, neutral or negative sentiment intensity or polarity by a new dictionary of words in Portuguese language and is extracted the sentiments. The calculation of sentiments has specific rules for verb tenses (present and past) and adverbs. The sentiments are extracted by means of adjectives, nouns, unigrams and associated words (bigrams and trigrams) that have a different meaning of single words. To validate the dictionary performance and new sentiments calculation mechanisms, the results are compared with an analysis tool of sentiments named of SentiStrength and are validated by subjective tests, with remote evaluators, with a technique named of crowdsourcing and machine learning. The study also analyzes the affection of sentences and proposes a metric called Brazillian Affective Metric (AFM-Br), that extracts emotions of anger, joy, sadness, surprise and disgust. The sentiment analysis solution and affection is applied in a music recommendation system, as a case study, which suggests content according to the emotional state of the person.
 
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RenataLopesRosa2015.pdf (972.56 Kbytes)
Date de Publication
2016-07-22
 
AVERTISSEMENT: Le matériau se réfère à des documents provenant de cette thèse ou mémoire. Le contenu de ces documents est la responsabilité de l'auteur de la thèse ou mémoire.
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  • RODRIGUEZ, DEMOSTENES ZEGARRA, ROSA, Renata Lopes, and Bressan, Graca. A billing system model for voice call service in cellular networks based on voice quality [doi:10.1109/ISCE.2013.6570267]. In 2013 IEEE 17th International Symposium on Consumer Electronics (ISCE), Hsinchu City. 2013 IEEE International Symposium on Consumer Electronics (ISCE). : IEEE, 2013.
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