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Music as an information object is a complex topic in the field of knowledge organization (KO), especially when the modeling and analysis occurs in an automated way. One of the techniques, derived from the field of Artificial Intelligence and Natural Language Processing (NLP) that has emerged as promising in this arena is the Sentiment Analysis (SA), or, alternatively, Opinion Mining; used to identify opinions and emotions in texts, evaluating them as positive or negative. This research present an experience of sentiment analysis with music lyrics. After building a database of lyrics in several languages made from crawling lyrics websites, the Brazilian Portuguese lyrics were morphosyntactically analysed. Then, the SA technique was applied to classify the corpus according to the emotional dimension, which resulted in a database of 3.2 GB, with 1616 lyrics in 38 languages, enriched with Part of Speech (POS) tagging and sentiment polarity for Portuguese. This experience has shown that the affective aspect can be measured or at least indicated by natural language processing, specifically via SA techniques. The results lead to the conclusion of the effectiveness of SA for music lyrics, attesting its applicability and contribution to the advancement of research in the field to the KO in this domain

Análise de sentimento aplicada ao estudo de letras de música