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ArtistRank – Analysis and Comparison of Artists Through the Characterization Data from Different Sources

  • Felipe Lopes de Melo Faria
  • Débora M. B. Paiva
  • Álvaro R. PereiraJr.
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9790)

Abstract

Understanding how artists, musical styles, and the music itself evolve over time is important when analysing the process of making music. In addition, it can help to study critical music artists that are in the top rankings and why. With the emergence of new ways in which communities are exposed to music, we see the need to reassess how the popularity of an artist is measured. It is noticed that traditional popularity rankings that model artists based only on disk sales and runs on the radio are not sufficient. The presence of numerous web services that allow user interaction in the world of music, whether listening online or watching the life of an artist more closely in digital media, has changed the dynamics of the music industry. Thus, this work proposes a methodology for music artists comparison based on how they perform on different music digital media available on the web. The methodology is also prepared to allow input data from mass media, so that a study case is presented using the TV media in order to properly assess the popularity of artists. Our case study shows that relevant rankings of music artists can be revealed by employing the proposed methodology.

Keywords

Data mining Rankings Digital media 

Notes

Acknowledgements

The authors thank the Federal University of Ouro Preto, Federal University of Mato Grosso do Sul, CAPES and Fundect for supporting the development of this research. Thanks also to the anonymous reviewers for their constructive comments, contributing to a better version of this article.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Felipe Lopes de Melo Faria
    • 1
  • Débora M. B. Paiva
    • 2
  • Álvaro R. PereiraJr.
    • 1
  1. 1.Departamento de ComputaçãoUniversidade Federal de Ouro PretoOuro PretoBrazil
  2. 2.Faculdade de ComputaçãoUniversidade Federal de Mato Grosso do SulCampo GrandeBrazil

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