MoodyLyrics

Author:

Çano Erion1,Morisio Maurizio1

Affiliation:

1. Polytechnic University of Turin, Duca degli Abruzzi, Turin, Italy

Publisher

ACM Press

Reference34 articles.

1. I. Bakker, T. van der Voordt, P. Vink, and J. de Boon. Pleasure, arousal, dominance: Mahrabian and russell revisited. Current Psychology, 33(3):405--421, 2014.

2. M. M. Bradley and P. J. Lang. A_ective norms for English words (ANEW): Stimuli, instruction manual, and affective ratings. Technical report, Center for Research in Psychophysiology, University of Florida, Gainesville, Florida, 1999.

3. E. Çano and M. Morisio. Characterization of public datasets for recommender systems. In Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI), 2015 IEEE 1st International Forum on, pages 249--257, Sept 2015.

4. O. Celma. Foafing the music bridging the semantic gap in music recommendation. In 5th International Semantic Web Conference (ISWC), Athens, GA, USA, 2016.

5. Tavel, P. 2007. Modeling and Simulation Design. AK Peters Ltd., Natick, MA.

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1. Mood Classification from Song Lyrics Using the Naive Bayes Algorithm, Support Vector Machine (SVM) and XGBoost;2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT);2024-07-04

2. Automatic music mood classification using multi-modal attention framework;Engineering Applications of Artificial Intelligence;2024-02

3. Soundscapes of morality: Linking music preferences and moral values through lyrics and audio;PLOS ONE;2023-11-29

4. A Sentiment Classification Model Based on Attention TIG-CNN-BiGRU;2023 International Conference on Culture-Oriented Science and Technology (CoST);2023-10-11

5. Learning Affective Responses to Music from Social Media Discourse;Signals and Communication Technology;2023-10-04

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