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

Junghyuk Lee; Jong Seok Lee

doi:10.1145/2802558.2814645

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

Junghyuk Lee, Jong Seok Lee

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 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 language	English
Title of host publication	SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015
Publisher	Association for Computing Machinery, Inc
Pages	3-6
Number of pages	4
ISBN (Electronic)	9781450337496
DOIs	https://doi.org/10.1145/2802558.2814645
Publication status	Published - 2015 Oct 30
Event	3rd Workshop on Speech, Language and Audio in Multimedia, SLAM 2015 - Brisbane, Australia Duration: 2015 Oct 30 → …

Publication series

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

Other

Other	3rd Workshop on Speech, Language and Audio in Multimedia, SLAM 2015
Country/Territory	Australia
City	Brisbane
Period	15/10/30 → …

Bibliographical note

Publisher Copyright:
© 2015 ACM.

All Science Journal Classification (ASJC) codes

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

Access to Document

10.1145/2802558.2814645

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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title = "Predicting music popularity patterns based on musical complexity and early stage popularity",

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.",

keywords = "Early stage popularity, Musical complexity, Popularity prediction",

author = "Junghyuk Lee and Lee, {Jong Seok}",

note = "Publisher Copyright: {\textcopyright} 2015 ACM.; 3rd Workshop on Speech, Language and Audio in Multimedia, SLAM 2015 ; Conference date: 30-10-2015",

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series = "SLAM 2015 - Proceedings of the 2015 Workshop on Speech, Language and Audio in Multimedia, co-located with ACM MM 2015",

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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 proceeding › Conference contribution

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N2 - 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.

AB - 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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KW - Popularity prediction

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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). doi: 10.1145/2802558.2814645

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

Abstract

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