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Sentiment analysis and topic modeling of Portuguese and Brazilian song lyrics through the years

Authors: D´Alva, Inês Mariana da Trindade;

Sentiment analysis and topic modeling of Portuguese and Brazilian song lyrics through the years

Abstract

As letras de uma música são uma rica fonte de informação, entre os diversos componentes no contexto musical. Com a sua identidade distinta e elementos narrativos, as letras têm o poder de transmitir mensagens profundas, com as emoções e os sentimentos retratados e os temas abordados. Ao longo do tempo, esses componentes líricos evoluíram, refletindo as mudanças nas dinâmicas da sociedade. Esta dissertação tem como objetivo estudar essas mudanças de sentimentos e tópicos no cenário nacional de Portugal e Brasil, abrangindo desde a década de 1960 até a década de 2020. Para alcançar estes objetivos, utilizamos uma abordagem baseada em léxico para análise de sentimentos e empregamos BERTopic e LDA para o modelo de tópicos. Os resultados das nossas pesquisas revelam um contraste emocional entre os dois países. As canções brasileiras predominantemente exalam positividade e sentimentos motivadores, enquanto que as canções portuguesas frequentemente carregam um tom de negatividade. Os tópicos extraídos das letras frequentemente se alinham com as experiências históricas e sociais de cada nação. No entanto, algumas instâncias mostram uma desconexão, onde as letras não refletem com precisão os períodos desafiadores, em termos de tópicos ou polaridades de sentimento. Isso sugere que os letristas podem usar as suas criações musicais como uma forma de escapar à realidade.

Music lyrics are a rich source of information, within the various components in the musical context. With their distinctive identity and narrative elements, lyrics have the power to convey profound messages, with the emotions and sentiments they portray and the themes addressed. Over time, these lyrical components have evolved, mirroring the changing dynamics of society. This dissertation aims to study these sentiment and topic changes in the national scope of Portugal and Brazil, spanning from the 1960s to the 2020s. To achieve this, we employ a lexicon-based approach for sentiment analysis and utilize BERTopic and LDA for topic modeling. The results of our research reveal an emotional contrast between the two countries. Brazilian songs predominantly exude positivity and uplifting sentiments, while Portuguese songs often carry a prevailing undertone of negativity. The extracted topics from the lyrics frequently align with each nation’s historical and societal experiences. However, some instances show a disconnect, where lyrics do not accurately mirror challenging periods in terms of topics or sentiment polarities. This suggests that lyricists may employ their musical creations as a form of escape from reality.

Country
Portugal
Keywords

Análise de sentimentos -- Sentiment analysis, Domínio/Área Científica::Ciências Sociais::Economia e Gestão, Music lyrics, Topic model, Text mining, Letras de música, Modelação de tópicos, Domínio/Área Científica::Engenharia e Tecnologia::Outras Engenharias e Tecnologias

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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