@inproceedings{2075c3b9b56d4fd99bd877501062683d,
title = "What is this song about anyway?: Automatic classification of subject using user interpretations and lyrics",
abstract = "Metadata research for music digital libraries has traditionally focused on genre. Despite its potential for improving the ability of users to better search and browse music collections, music subject metadata is an unexplored area. The objective of this study is to expand the scope of music metadata research, in particular, by exploring music subject classification based on user interpretations of music. Furthermore, we compare this previously unexplored form of user data to lyrics at subject prediction tasks. In our experiment, we use datasets consisting of 900 songs annotated with user interpretations. To determine the significance of performance differences between the two sources, we applied Friedman's ANOVA test on the classification accuracies. The results show that user-generated interpretations are significantly more useful than lyrics as classification features (p < 0.05). The findings support the possibility of exploiting various existing sources for subject metadata enrichment in music digital libraries.",
keywords = "Data mining, Lyrics, Metadata, Music, Music Information Retrieval, Subject, Text classification, User-generated content",
author = "Kahyun Choi and Lee, {Jin Ha} and Downie, {J. Stephen}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 14th IEEE/ACM Joint Conference on Digital Libraries, JCDL 2014 ; Conference date: 08-09-2014 Through 12-09-2014",
year = "2014",
month = dec,
day = "1",
doi = "10.1109/JCDL.2014.6970221",
language = "English (US)",
series = "Proceedings of the ACM/IEEE Joint Conference on Digital Libraries",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "453--454",
booktitle = "2014 IEEE/ACM Joint Conference on Digital Libraries, JCDL 2014",
address = "United States",
}