Toward a Musical Sentiment (MuSe) Dataset for Affective Distant Hearing

Description

In this short paper we present work in progress that tries to leverage crowdsourced music metadata
and crowdsourced affective word norms to create a comprehensive dataset of music emotions, which
can be used for sentiment analyses in the music domain. We combine a mixture of different data
sources to create a new dataset of 90,408 songs with their associated embeddings in Russell’s model
of affect, with the dimensions valence, dominance and arousal. In addition, we provide a Spotify ID
for the songs, which can be used to add more metadata to the dataset via the Spotify API.

Links & Downloads

1. urn:nbn:de:bsz:15-qucosa2-921665
2. https://ul.qucosa.de/id/qucosa%3A92166
3. https://ul.qucosa.de/api/qucosa%3A92166/attachment/ATT-0/

Tags

info:eu-repo/classification/ddc/006

ddc:006

info:eu-repo/classification/ddc/780

ddc:780

Additional Fields

Identifer	oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:92166
Date	20 June 2024
Creators	Akiki, Christopher, Burghardt, Manuel
Publisher	CEUR-WS.org
Source Sets	Hochschulschriftenserver (HSSS) der SLUB Dresden
Language	English
Detected Language	English
Type	info:eu-repo/semantics/publishedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text
Rights	info:eu-repo/semantics/openAccess