Topic modeling applied to business research: A latent dirichlet allocation (LDA)-based classification for organization studies

Carlos Vílchez Román, Farita Huamán Delgado, Sol Sanguinetti Cordero

Producción científica: Contribución a una revistaArtículo (Contribución a Revista)revisión exhaustiva

Resumen

More than 1.5 million academic documents are published each year, and this trend shows an incremental tendency for the following years. One of the main challenges for the academic community is how to organize this huge volume of documentation to have a sense of the knowledge frontier. In this study we applied Latent Dirichlet Allocation (LDA) techniques to identify primary topics in organization studies, and analyzed the relationships between academic impact and belonging to the topics detected by LDA.
Idioma originalInglés estadounidense
PublicaciónDefault journal
DOI
EstadoPublicada - 1 ene. 2019
Publicado de forma externa

COAR

  • Artículo de conferencia

Temas Repositorio Ulima

  • Empresas
  • Enterprises

Huella

Profundice en los temas de investigación de 'Topic modeling applied to business research: A latent dirichlet allocation (LDA)-based classification for organization studies'. En conjunto forman una huella única.

Citar esto