Predicting music popularity patterns based on musical complexity and early stage popularity

Junghyuk Lee, Jong Seok Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This paper investigates the problem of predicting popularity of music. In particular, we consider musical complexity as a cue that can be extracted from the audio signal and used for popularity prediction. In addition, we examine the effectiveness of the early stage popularity for long-term popularity prediction. We formulate the popularity prediction problem as a classification problem predicting popularity evolution patterns in a music ranking chart, such as the highest rank of a song over the whole time period, the growth/declination rate in the chart, the duration for which the song appears in the chart, etc. We conduct an experiment with the data collected from the Billboard Rock Songs Chart for about five years. It is found that the two types of features are effective for predicting popularity patterns when used together.

Original languageEnglish
Title of host publicationSLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015
PublisherAssociation for Computing Machinery, Inc
Pages3-6
Number of pages4
ISBN (Electronic)9781450337496
DOIs
Publication statusPublished - 2015 Oct 30
Event3rd Workshop on Speech, Language and Audio in Multimedia, SLAM 2015 - Brisbane, Australia
Duration: 2015 Oct 30 → …

Publication series

NameSLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015

Other

Other3rd Workshop on Speech, Language and Audio in Multimedia, SLAM 2015
CountryAustralia
CityBrisbane
Period15/10/30 → …

Fingerprint

Music
popularity
music
song
Rocks
Cues
Experiments
ranking
Growth
experiment

All Science Journal Classification (ASJC) codes

  • Otorhinolaryngology
  • Linguistics and Language
  • Speech and Hearing
  • Software
  • Computer Vision and Pattern Recognition

Cite this

Lee, J., & Lee, J. S. (2015). Predicting music popularity patterns based on musical complexity and early stage popularity. In SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015 (pp. 3-6). (SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015). Association for Computing Machinery, Inc. https://doi.org/10.1145/2802558.2814645
Lee, Junghyuk ; Lee, Jong Seok. / Predicting music popularity patterns based on musical complexity and early stage popularity. SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015. Association for Computing Machinery, Inc, 2015. pp. 3-6 (SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015).
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abstract = "This paper investigates the problem of predicting popularity of music. In particular, we consider musical complexity as a cue that can be extracted from the audio signal and used for popularity prediction. In addition, we examine the effectiveness of the early stage popularity for long-term popularity prediction. We formulate the popularity prediction problem as a classification problem predicting popularity evolution patterns in a music ranking chart, such as the highest rank of a song over the whole time period, the growth/declination rate in the chart, the duration for which the song appears in the chart, etc. We conduct an experiment with the data collected from the Billboard Rock Songs Chart for about five years. It is found that the two types of features are effective for predicting popularity patterns when used together.",
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Lee, J & Lee, JS 2015, Predicting music popularity patterns based on musical complexity and early stage popularity. in SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015. SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015, Association for Computing Machinery, Inc, pp. 3-6, 3rd Workshop on Speech, Language and Audio in Multimedia, SLAM 2015, Brisbane, Australia, 15/10/30. https://doi.org/10.1145/2802558.2814645

Predicting music popularity patterns based on musical complexity and early stage popularity. / Lee, Junghyuk; Lee, Jong Seok.

SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015. Association for Computing Machinery, Inc, 2015. p. 3-6 (SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Lee J, Lee JS. Predicting music popularity patterns based on musical complexity and early stage popularity. In SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015. Association for Computing Machinery, Inc. 2015. p. 3-6. (SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015). https://doi.org/10.1145/2802558.2814645