MuSe: The Musical Sentiment Dataset

Abstract

The MuSe (Music Sentiment) dataset contains sentiment information for 90,001 songs. We computed scores for the affective dimensions of valence, dominance, and arousal, based on the user-generated tags that are available for each song via Last.fm. In addition, we provide artist, title and genre metadata, and a MusicBrainz ID and a Spotify ID, which allow researchers to extend the dataset with further metadata.

Keywords

• music information retrieval
• music emotion recognition
• music sentiment
• music dataset
• sentiment analysis