TY - GEN
T1 - Sentiment Analysis of Song Lyrics Using Clustering
AU - Vásquez-Leon, Miguel
AU - Ugarte, Willy
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Music often helps people to relax and have fun times. However, the search for this in a personalized way based on the feelings of the users is not present in the main search engines. The closest thing to this would be the playlists created arbitrarily by other users. For this reason, we propose a method that allows us to label artists representing different feelings according to their lyrics.
AB - Music often helps people to relax and have fun times. However, the search for this in a personalized way based on the feelings of the users is not present in the main search engines. The closest thing to this would be the playlists created arbitrarily by other users. For this reason, we propose a method that allows us to label artists representing different feelings according to their lyrics.
KW - K-means
KW - Machine learning
KW - NLP
KW - Psychology
UR - https://www.scopus.com/pages/publications/85111400230
U2 - 10.1007/978-3-030-75680-2_38
DO - 10.1007/978-3-030-75680-2_38
M3 - Contribución a la conferencia
AN - SCOPUS:85111400230
SN - 9783030756796
T3 - Smart Innovation, Systems and Technologies
SP - 342
EP - 350
BT - Proceedings of the 6th Brazilian Technology Symposium, BTSym 2020 - Emerging Trends and Challenges in Technology
A2 - Iano, Yuzo
A2 - Saotome, Osamu
A2 - Kemper, Guillermo
A2 - Mendes de Seixas, Ana Claudia
A2 - Gomes de Oliveira, Gabriel
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th Brazilian Technology Symposium, BTSym 2020
Y2 - 26 October 2020 through 28 October 2020
ER -