Título:
Applying data mining for sentiment analysis in music.
Applying data mining for sentiment analysis in music.
Autores:
Martín Gómez, Lucía; Navarro Cáceres, María
Libro:
Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017. Advances in Intelligent Systems and Computing. Volumen 619, pp. 198-205.
Fecha de Publicación:
16 July 2017
ISBN:
978-3-319-61577-6 (Print), 978-3-319-61578-3 (Online)
Listening to music can affect people emotions. They can experience simultaneous feelings, such as happiness and hope, or sadness and angry, when a song is being played. However, infering emotions that can be caused by a musical fragment is a complex task. To deduce relationships between feelings and music, we propose a sentiment analysis method based on data mining. In particular, different musical features are extracted and classified to analyze the influence of some music parameters on human emotions. In this process, data mining algorithms such as Random k-Labelsets, Multi-Label k-Nearest Neighbors or Apriori have been essential for the success of our proposal.