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Measuring success in streaming platforms


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Título :
Measuring success in streaming platforms
Autor :
Gonçalves Dosantos, Juan Carlos
Martínez, Ricardo
Sánchez Soriano, Joaquín
Editor :
Elsevier
Departamento:
Departamentos de la UMH::Estadística, Matemáticas e Informática
Fecha de publicación:
2025
URI :
https://hdl.handle.net/11000/40191
Resumen :
Digital streaming platforms , including Twitch, Spotify, Netflix, Disney+, and Kindle, have emerged as major sources of entertainment with significant growth potential. Many of these platforms distribute royalties among streamers, artists, producers, or writers based on their impact. In this paper, we measure the relevance of each of these contributors to the overall success of the platform, which can play a key role in revenue allocation. We perform an axiomatic analysis to provide normative foundations for four relevance metrics: the uniform, the subscriber-uniform, the proportional, and the subscriber-proportional indicators. The last two indicators implement the so-called pro-rata and user-centric models, which are extensively applied to distribute revenues in the music streaming market. The axioms we propose formalize different principles of fairness, stability, and non-manipulability, and are tailor-made for the streaming context. We complete our analysis with a case study that measures the influence of the 19 most-followed streamers worldwide on the Twitch platform.
Palabras clave/Materias:
measure
relevance
proportionality
streaming
axiom
Área de conocimiento :
CDU: Ciencias puras y naturales: Matemáticas
CDU: Ciencias sociales: Demografía. Sociología. Estadística: Estadística
CDU: Ciencias sociales: Economía
Tipo de documento :
info:eu-repo/semantics/article
Derechos de acceso:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.1016/j.jebo.2025.106941
Publicado en:
Journal of Economic Behavior & Organization
Aparece en las colecciones:
Artículos - Estadística, Matemáticas e Informática



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.