Understanding Musical Success Beyond Hit Songs: Characterization and Analyses of Musical Careers
Resumo
Streaming brought the high data availability over the web associated with music consumption and listener preference. With such data, we can extract relevant knowledge, such as what can lead some songs to success and others not. In this scenario, Hit Song Science emerged, an area of study focused on revealing the dynamics of success in the music industry. Collecting hits can lead artists to experience periods of success far beyond the "ordinary" periods known as Hot Streaks. In this sense, understanding the factors of how the different profiles of artists stand out and reach their most successful periods can be crucial for the music industry, which deals with the constant natural evolution of the market and needs to reinvent itself to satisfy the desires of its consumers: connect successful music and artists. Thus, this thesis aims to identify the characteristics that lead artists to reach their most successful periods.
Palavras-chave:
Hit Song Science, Music Information Retrieval, Musical Success
Referências
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Lu Liu et al. 2018. Hot streaks in artistic, cultural, and scientific careers. Nature 559, 7714 (2018), 396–399. DOI: 10.1038/s41586-018-0315-8
Lu Liu, Nima Dehmamy, Jillian Chown, C. Lee Giles, and Dashun Wang. 2021. Understanding the onset of hot streaks across artistic, cultural, and scientific careers. Nature Communications 12, 1 (Sept. 2021), 5392. DOI: 10.1038/s41467-021-25477-8
Gabriel P. Oliveira, Mariana O. Silva, Danilo B. Seufitelli, Gabriel R. G. Barbosa, Bruna C. Melo, and Mirella M. Moro. 2023. Hot streaks in the music industry: identifying and characterizing above-average success periods in artists’ careers. Scientometrics 128, 11 (2023), 6029–6046. DOI: 10.1007/s11192-02304835-x
François Pachet and Pierre Roy. 2008. Hit Song Science Is Not Yet a Science. In International Conference on Music Information Retrieval. ISMIR, Philadelphia, USA, 355–360.
Arthur C. Serra, Antonio José G. Busson, Álan L. V. Guedes, and Sérgio Colcher. 2021. Quality Enhancement of Highly Degraded Music Using Deep LearningBased Prediction Models for Lost Frequencies. In Procs Braz Symp Multimedia and the Web. ACM, Belo Horizonte, Brazil, 205–211. DOI: 10.1145/3470482.3479635
Danilo B. Seufitelli, Gabriel P. Oliveira, Mariana O. Silva, Gabriel R. G. Barbosa, Bruna C. Melo, Juliana E. Botelho, Luiza de Melo-Gomes, and Mirella M. Moro. 2022. From Compact Discs to Streaming: A Comparison of Eras within the Brazilian Market. Revista Vórtex 10, 1 (2022).
Mariana O. Silva, Gabriel P. Oliveira, Danilo B. Seufitelli, Anisio Lacerda, and Mirella M. Moro. 2022. Collaboration as a Driving Factor for Hit Song Classification. In Procs Braz Symp Multimedia and the Web. Curitiba, Brazil, 66–74. DOI: 10.1145/3539637.3556993
Gabriel Barbosa, Bruna Melo, Gabriel Oliveira, Mariana Silva, Danilo Seufitelli, and Mirella Moro. 2021. Hot Streaks in the Brazilian Music Market: A Comparison Between Physical and Digital Eras. In Anais do XVIII Simpósio Brasileiro de Computação Musical. SBC, 152–159. DOI: 10.5753/sbcm.2021.19440
Alexandra Covaci. 2023. Bytes and Rhythms – Delving into the Tech-Driven Evolution of Food and Music. In Procs Braz Symp Multimedia and the Web. ACM, Ribeirão Preto, Brazil, 1–2. DOI: 10.1145/3617023.3617024
Angelo Cesar Mendes da Silva, Diego Furtado Silva, and Ricardo Marcondes Marcacini. 2020. 4MuLA: A Multitask, Multimodal, and Multilingual Dataset of Music Lyrics and Audio Features. In Procs Braz Symp Multimedia and the Web. ACM, São Luís, Brazil, 145–148. DOI: 10.1145/3428658.3431089
Darryll Hendricks, Jayendu Patel, and Richard Zeckhauser. 1993. Hot hands in mutual funds: Short-run persistence of relative performance, 1974–1988. The Journal of finance 48, 1 (1993), 93–130.
Milan Janosov, Federico Battiston, and Roberta Sinatra. 2020. Success and luck in creative careers. The European Physical Journal Data Science 9, 1 (2020), 9. DOI: 10.1140/epjds/s13688-020-00227-w
Lu Liu et al. 2018. Hot streaks in artistic, cultural, and scientific careers. Nature 559, 7714 (2018), 396–399. DOI: 10.1038/s41586-018-0315-8
Lu Liu, Nima Dehmamy, Jillian Chown, C. Lee Giles, and Dashun Wang. 2021. Understanding the onset of hot streaks across artistic, cultural, and scientific careers. Nature Communications 12, 1 (Sept. 2021), 5392. DOI: 10.1038/s41467-021-25477-8
Gabriel P. Oliveira, Mariana O. Silva, Danilo B. Seufitelli, Gabriel R. G. Barbosa, Bruna C. Melo, and Mirella M. Moro. 2023. Hot streaks in the music industry: identifying and characterizing above-average success periods in artists’ careers. Scientometrics 128, 11 (2023), 6029–6046. DOI: 10.1007/s11192-02304835-x
François Pachet and Pierre Roy. 2008. Hit Song Science Is Not Yet a Science. In International Conference on Music Information Retrieval. ISMIR, Philadelphia, USA, 355–360.
Arthur C. Serra, Antonio José G. Busson, Álan L. V. Guedes, and Sérgio Colcher. 2021. Quality Enhancement of Highly Degraded Music Using Deep LearningBased Prediction Models for Lost Frequencies. In Procs Braz Symp Multimedia and the Web. ACM, Belo Horizonte, Brazil, 205–211. DOI: 10.1145/3470482.3479635
Danilo B. Seufitelli, Gabriel P. Oliveira, Mariana O. Silva, Gabriel R. G. Barbosa, Bruna C. Melo, Juliana E. Botelho, Luiza de Melo-Gomes, and Mirella M. Moro. 2022. From Compact Discs to Streaming: A Comparison of Eras within the Brazilian Market. Revista Vórtex 10, 1 (2022).
Mariana O. Silva, Gabriel P. Oliveira, Danilo B. Seufitelli, Anisio Lacerda, and Mirella M. Moro. 2022. Collaboration as a Driving Factor for Hit Song Classification. In Procs Braz Symp Multimedia and the Web. Curitiba, Brazil, 66–74. DOI: 10.1145/3539637.3556993
Publicado
14/10/2024
Como Citar
SEUFITELLI, Danilo Boechat; MORO, Mirella M..
Understanding Musical Success Beyond Hit Songs: Characterization and Analyses of Musical Careers. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 30. , 2024, Juiz de Fora/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 23-24.
ISSN 2596-1683.
DOI: https://doi.org/10.5753/webmedia_estendido.2024.244326.
