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Hot streaks in the music industry: identifying and characterizing above-average success periods in artists’ careers

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Abstract

In this work, we reveal fundamental patterns that appear in individual musical careers. Such careers may go through ups and downs depending on the current market moment and release of new songs. In particular, they face hot streak periods in which high-impact bursts occur in sequence. Identifying such periods and even predicting them may help in other practical issues, which include foreseeing success and recommending artists. After modeling artists’ careers as time series, we find a general trend of clustering within the most successful weeks, which justifies the applicability of the concept of hot streaks. Hence, we use a specific methodology for identifying hot streaks, whose evaluation results reveal meaningful patterns for artists of different genres. We also confirm the career peaks of artists appear and disappear progressively over time. Overall, our findings shed light on the science of musical success as we observe the temporal evolution of artists’ careers and their hot streaks.

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Data availability

Our dataset, called Music-oriented Hot Streak Information Collection (MUHSIC), is publicly available in Zenodo (Oliveira et al., 2021a). This dataset has been presented previously in Oliveira et al. (2021b, 2022). Such works focus on the building process of the dataset and its characterization only (i.e., they are not related with Hot Streaks). In addition, Barbosa et al. (2021) and Seufitelli et al. (2022) use MUHSIC-BR, another dataset built with the same methodology but with data from the Brazilian music market, which is not addressed in this paper.

Notes

  1. International Olympic Committee: https://www.olympic.org/athletes.

  2. IFPI Global Music Report 2021: https://gmr.ifpi.org/.

  3. Billboard: https://bit.ly/3hfzMJ0.

  4. Source: https://www.billboard.com/charts/hot-100/2016-07-02.

  5. tslearn: https://github.com/tslearn-team/tslearn/.

  6. Recording Academy Grammy Awards: https://www.grammy.com/.

  7. Greatest of All Time: https://www.billboard.com/charts/greatest-of-all-time-artists.

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Acknowledgements

This article results from an academic master’s thesis finished in 2021 in the Graduate Program in Computer Science of the Federal University of Minas Gerais (Oliveira, 2021).

Funding

This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil.

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Contributions

All authors contributed to the study's conception and design. Material preparation and data collection were performed by Gabriel P. Oliveira. Analyses were performed by all authors. The first draft of the manuscript was mostly written by Gabriel P. Oliveira, Mariana O. Silva, and Danilo B. Seufitelli. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. The overall project was managed by Mirella M. Moro.

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Correspondence to Mirella M. Moro.

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Oliveira, G.P., Silva, M.O., Seufitelli, D.B. et al. Hot streaks in the music industry: identifying and characterizing above-average success periods in artists’ careers. Scientometrics 128, 6029–6046 (2023). https://doi.org/10.1007/s11192-023-04835-x

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