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

doi:10.1007/978-3-030-11680-4_21

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 revista › Artículo (Contribución a Revista) › revisión exhaustiva

3 Citas (Scopus)

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 original	Inglés estadounidense
Publicación	Default journal
DOI	https://doi.org/10.1007/978-3-030-11680-4_21
Estado	Publicada - 1 ene. 2019
Publicado de forma externa	Sí

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abstract = "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.",

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AB - 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.

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

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