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SportMiner  

Text Mining and Topic Modeling for Sport Science Literature
View on CRAN: Click here


Download and install SportMiner package within the R console
Install from CRAN:
install.packages("SportMiner")

Install from Github:
library("remotes")
install_github("cran/SportMiner")

Install by package version:
library("remotes")
install_version("SportMiner", "0.1.0")



Attach the package and use:
library("SportMiner")
Maintained by
Praveen D Chougale
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-01-17
Latest Update: 2026-01-17
Description:
A comprehensive toolkit for mining, analyzing, and visualizing scientific literature in sport science domains. Provides functions for retrieving abstracts from 'Scopus', preprocessing text data, performing advanced topic modeling using Latent Dirichlet Allocation ('LDA'), Structural Topic Models ('STM'), and Correlated Topic Models ('CTM'), and creating publication-ready visualizations including keyword co-occurrence networks and topic trends. For methodological details see Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993> for 'LDA', Roberts et al. (2014) <doi:10.1111/ajps.12103> for 'STM', and Blei and Lafferty (2007) <doi:10.1214/07-AOAS114> for 'CTM'.
How to cite:
Praveen D Chougale (2026). SportMiner: Text Mining and Topic Modeling for Sport Science Literature. R package version 0.1.0, https://cran.r-project.org/web/packages/SportMiner. Accessed 12 Sep. 2026.
Previous versions and publish date:
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Complete documentation for SportMiner
Functions, R codes and Examples using the SportMiner R package
Full SportMiner package functions and examples
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