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Detección de factores relevantes en redes sociales incorporando información de expertos
[Incorporating Expert Judgment for Detecting Relevant Factors in SocialNetworks Undetected by Ordinary Methods]

Author

Listed:
  • José María Pérez-Sánchez

    (Universidad de Las Palmas de Gran Canaria)

  • María Acosta García

    (Universidad de Granada)

  • Emilio Gómez-Déniz

    (Universidad de Las Palmas de Gran Canaria)

Abstract

La mayoría de las empresas utilizan las redes sociales como canales de comunicación debido a los beneficios empresariales que pueden proporcionar. Este artículo se centra en el impacto de las redes sociales en una fundación española dedicada a la innovación y la difusión del conocimiento, y en cómo afectan a sus principales eventos y actividades. Examinamos los factores subyacentes a un retuit en Twitter o una compartición en Facebook con el fin de analizar la difusión de los eventos principales de esta fundación. Se realizaron comparaciones con tres modelos estadísticos (regresión estándar yregresión bayesiana con distribución a priori informativa y no informativa). Concluimos que la ventaja que ofrece la metodología bayesiana sobre la clásica se demuestra mediante la incorporación de información colateral, generalmente proporcionada por expertos, lo que permite refinar el modelo y obtener conclusiones que, de otro modo, no podrían ser identificadas. Esta conclusión puede tener implicaciones significativas para las empresas que utilizan redes sociales.

Suggested Citation

  • José María Pérez-Sánchez & María Acosta García & Emilio Gómez-Déniz, 2024. "Detección de factores relevantes en redes sociales incorporando información de expertos [Incorporating Expert Judgment for Detecting Relevant Factors in SocialNetworks Undetected by Ordinary Method," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 38, pages 1-13, December.
    • Handle: RePEc:pab:rmcpee:v:38:y:2024:p:1-13
    DOI: https://doi.org/10.46661/rev.metodoscuant.econ.empresa.8135
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    More about this item

    Keywords

    Inferencia bayesiana; simulación MCMC; distribución a priori informativa; redes sociales; Bayesian inference; MCMC simulation methods; informative prior distributions; social networks;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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