SportMiner: Text Mining and Topic Modeling for Sport Science Literature

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'.

Version: 0.1.0
Depends: R (≥ 4.0.0)
Imports: rscopus, dplyr, tidytext, topicmodels, stm, ggplot2, rlang, SnowballC, scales, textmineR, Matrix, tidyr, ggraph, igraph, widyr, magrittr, slam
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, withr
Published: 2026-01-17
DOI: 10.32614/CRAN.package.SportMiner (may not be active yet)
Author: Praveen D Chougale [aut, cre], Usha Ananthakumar [aut]
Maintainer: Praveen D Chougale <praveenmaths89 at gmail.com>
BugReports: https://github.com/praveenmaths89/SportMiner/issues
License: MIT + file LICENSE
URL: https://github.com/praveenmaths89/SportMiner
NeedsCompilation: no
Citation: SportMiner citation info
Materials: README, NEWS
CRAN checks: SportMiner results

Documentation:

Reference manual: SportMiner.html , SportMiner.pdf
Vignettes: SportMiner: Text Mining and Topic Modeling for Sport Science Literature (source, R code)
Getting Started with SportMiner (source, R code)

Downloads:

Package source: SportMiner_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): SportMiner_0.1.0.tgz, r-oldrel (arm64): SportMiner_0.1.0.tgz, r-release (x86_64): SportMiner_0.1.0.tgz, r-oldrel (x86_64): SportMiner_0.1.0.tgz

Linking:

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