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Topic Modeling Applied to Business Research: A Latent Dirichlet Allocation (LDA)-Based Classification for Organization Studies

  • Carlos Vílchez-RománEmail author
  • Farita Huamán-Delgado
  • Sol Sanguinetti-Cordero
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 898)

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.

Keywords

Text mining Organization studies Topic modeling 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.CENTRUM Católica Graduate Business School (CCGBS)LimaPeru
  2. 2.Pontificia Universidad Católica del Perú (PUCP)LimaPeru
  3. 3.Universidad Nacional Mayor de San Marcos (UNMSM)LimaPeru
  4. 4.School of CommunicationsUniversidad de Lima (UL)LimaPeru
  5. 5.Environment Technology Institute (ETI)LimaPeru

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