Title
Topic modeling applied to business research: A latent dirichlet allocation (LDA)-based classification for organization studies
Date Issued
01 January 2019
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Springer Verlag
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.
Start page
212
End page
219
Volume
898
Language
English
OCDE Knowledge area
Ciencias de la computación Ingeniería de sistemas y comunicaciones
Scopus EID
2-s2.0-85063435611
ISBN
9783030116798
Source
Communications in Computer and Information Science
ISSN of the container
18650929
Sponsor(s)
BBVA, Peru North American Chapter of the ACL, USA Telefónica del Perú, Peru
Sources of information: Directorio de Producción Científica Scopus