Collaboration-Aware Hit Song Prediction
In a streaming-oriented era, predicting which songs will be successful is a significant challenge for the music industry. Indeed, there are many efforts in determining the driving factors that contribute to a song’s success, and one potential solution could be incorporating artistic collaborations,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Brazilian Computer Society
2023-06-01
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| Series: | Journal on Interactive Systems |
| Subjects: | |
| Online Access: | https://sol.sbc.org.br/journals/index.php/jis/article/view/3137 |
| _version_ | 1827914781429858304 |
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| author | Mariana O. Silva Gabriel P. Oliveira Danilo B. Seufitelli Mirella M. Moro |
| author_facet | Mariana O. Silva Gabriel P. Oliveira Danilo B. Seufitelli Mirella M. Moro |
| author_sort | Mariana O. Silva |
| collection | DOAJ |
| description |
In a streaming-oriented era, predicting which songs will be successful is a significant challenge for the music industry. Indeed, there are many efforts in determining the driving factors that contribute to a song’s success, and one potential solution could be incorporating artistic collaborations, as it allows for a wider audience reach. Therefore, we propose a multi-perspective approach that includes collaboration between artists as a factor for hit song prediction. Specifically, by combining online data from Billboard and Spotify, we tackle the problem as both classification and hit song placement tasks, applying five different model variants. Our results show that relying only on music-related features is not enough, whereas models that also consider collaboration features produce better results.
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| first_indexed | 2024-03-13T02:50:07Z |
| format | Article |
| id | doaj.art-109564f049a04fe59b5bee85fa26619d |
| institution | Directory Open Access Journal |
| issn | 2763-7719 |
| language | English |
| last_indexed | 2024-03-13T02:50:07Z |
| publishDate | 2023-06-01 |
| publisher | Brazilian Computer Society |
| record_format | Article |
| series | Journal on Interactive Systems |
| spelling | doaj.art-109564f049a04fe59b5bee85fa26619d2023-06-28T13:20:39ZengBrazilian Computer SocietyJournal on Interactive Systems2763-77192023-06-0114110.5753/jis.2023.3137Collaboration-Aware Hit Song PredictionMariana O. Silva0Gabriel P. Oliveira1Danilo B. Seufitelli2Mirella M. Moro3Universidade Federal de Minas GeraisUniversidade Federal de Minas GeraisUniversidade Federal de Minas GeraisUniversidade Federal de Minas Gerais In a streaming-oriented era, predicting which songs will be successful is a significant challenge for the music industry. Indeed, there are many efforts in determining the driving factors that contribute to a song’s success, and one potential solution could be incorporating artistic collaborations, as it allows for a wider audience reach. Therefore, we propose a multi-perspective approach that includes collaboration between artists as a factor for hit song prediction. Specifically, by combining online data from Billboard and Spotify, we tackle the problem as both classification and hit song placement tasks, applying five different model variants. Our results show that relying only on music-related features is not enough, whereas models that also consider collaboration features produce better results. https://sol.sbc.org.br/journals/index.php/jis/article/view/3137Hit Song ScienceHit Song PredictionMusic Information RetrievalMusic Data MiningMachine Learning |
| spellingShingle | Mariana O. Silva Gabriel P. Oliveira Danilo B. Seufitelli Mirella M. Moro Collaboration-Aware Hit Song Prediction Journal on Interactive Systems Hit Song Science Hit Song Prediction Music Information Retrieval Music Data Mining Machine Learning |
| title | Collaboration-Aware Hit Song Prediction |
| title_full | Collaboration-Aware Hit Song Prediction |
| title_fullStr | Collaboration-Aware Hit Song Prediction |
| title_full_unstemmed | Collaboration-Aware Hit Song Prediction |
| title_short | Collaboration-Aware Hit Song Prediction |
| title_sort | collaboration aware hit song prediction |
| topic | Hit Song Science Hit Song Prediction Music Information Retrieval Music Data Mining Machine Learning |
| url | https://sol.sbc.org.br/journals/index.php/jis/article/view/3137 |
| work_keys_str_mv | AT marianaosilva collaborationawarehitsongprediction AT gabrielpoliveira collaborationawarehitsongprediction AT danilobseufitelli collaborationawarehitsongprediction AT mirellammoro collaborationawarehitsongprediction |