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Mariana O Silva

Biographic Data

ID7398169
NAMEMariana O Silva
GIVEN NAMESMariana
FAMILY NAMEO Silva
SIGNATURESILVA M O
AFFILIATIONSUniversidade Federal de Minas Gerais
ORCID0000-0003-0110-9924
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Temporal Success Analyses in Music Collaboration Networks

    Open Access•Mirella M MORO, Mariana O Silva et al.•ARTICLE•Revista Vórtex•2023

    Collaboration is a part of the music industry and has increased over recent decades; but little do we know about its effects on success and evolution. Our goal is to analyze how success has evolved over collaboration networks and compare its global scenario to a local, thriving one: the Brazilian music industry. Specifically, we build collaboration networks from data collected from Spotify's Global and Brazilian daily charts, analyze them and ide…

  • Hot streaks in the music industry

    Open Access•Glaucimara Pires Oliveira, Gabriel P Oliveira et al.•ARTICLE•Scientometrics•2023

  • Hit song science

    Danilo B Seufitelli, Glaucimara Pires Oliveira et al.•ARTICLE•Journal of New Music Research•2023

    Hit Song Science (HSS) is an emerging topic that aims to unveil the success dynamics within the music industry. Considering the growth of the area, we provide a comprehensive study with a complete review of the main topics of this interdisciplinary field from a computer science perspective. We also define a generic workflow for HSS, introduce taxonomies for success measures and musical features, and categorize the main current learning algorithms…

  • From Compact Discs to Streaming

    Open Access•Danilo B Seufitelli, Glaucimara Pires Oliveira et al.•ARTICLE•Revista Vórtex•2022

    The music industry has undergone many changes in the last few decades, notably since vinyl, cassettes and compact discs faded away as streaming platforms took the world by storm. This Digital evolution has made huge volumes of data about music consumption available. Based on such data, we perform cross-era comparisons between Physical and Digital media within the music market in Brazil. First, we build artists' success time series to detect and c…

No prominent works on this page.

  • From Compact Discs to Streaming

    Open Access•Danilo B Seufitelli, Glaucimara Pires Oliveira et al.•ARTICLE•Revista Vórtex•2022

    The music industry has undergone many changes in the last few decades, notably since vinyl, cassettes and compact discs faded away as streaming platforms took the world by storm. This Digital evolution has made huge volumes of data about music consumption available. Based on such data, we perform cross-era comparisons between Physical and Digital media within the music market in Brazil. First, we build artists' success time series to detect and c…

  • Temporal Success Analyses in Music Collaboration Networks

    Open Access•Mirella M MORO, Mariana O Silva et al.•ARTICLE•Revista Vórtex•2023

    Collaboration is a part of the music industry and has increased over recent decades; but little do we know about its effects on success and evolution. Our goal is to analyze how success has evolved over collaboration networks and compare its global scenario to a local, thriving one: the Brazilian music industry. Specifically, we build collaboration networks from data collected from Spotify's Global and Brazilian daily charts, analyze them and ide…

  • Hot streaks in the music industry

    Open Access•Glaucimara Pires Oliveira, Gabriel P Oliveira et al.•ARTICLE•Scientometrics•2023

  • Hit song science

    Danilo B Seufitelli, Glaucimara Pires Oliveira et al.•ARTICLE•Journal of New Music Research•2023

    Hit Song Science (HSS) is an emerging topic that aims to unveil the success dynamics within the music industry. Considering the growth of the area, we provide a comprehensive study with a complete review of the main topics of this interdisciplinary field from a computer science perspective. We also define a generic workflow for HSS, introduce taxonomies for success measures and musical features, and categorize the main current learning algorithms…

Computer Science (4 works) · Data science (3 works) · Visual arts (3 works) · Art (2 works) · Artificial Intelligence (2 works) · History (2 works) · Music and Audio Processing (2 works) · Music industry (2 works) · Music Technology and Sound Studies (2 works) · Musical (2 works)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae