LDAShiny: Interactive Topic Modeling and Bibliometric Analysis via Shiny

Provides a 'Shiny' graphical interface for the complete workflow of Latent Dirichlet Allocation (LDA) topic modelling on bibliometric data from Scopus and Web of Science. Steps include data import and deduplication, text preprocessing (stopword removal, stemming, n-grams, sparse-term filtering), statistical inference to select the optimal number of topics via coherence, final model training, and topic trend analysis over time using linear regression. All results can be exported as Excel files, RDS objects, and publication-quality plots.

Version:	1.0.0
Depends:	R (≥ 4.1.0)
Imports:	colourpicker, config (≥ 0.3.1), dplyr, DT, ggplot2, golem (≥ 0.4.0), Matrix, openxlsx, quanteda, RColorBrewer, readxl, shiny (≥ 1.7.0), shinybusy, shinydashboard, shinyjs, shinyWidgets, slam, SnowballC, stopwords, textmineR, tibble, tidyr, tm, wordcloud, broom, parallel, stats, utils, grDevices
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0), withr
Published:	2026-06-08
DOI:	10.32614/CRAN.package.LDAShiny
Author:	Javier De La Hoz-M [aut, cre]
Maintainer:	Javier De La Hoz-M <jdelahoz at unimagdalena.edu.co>
License:	GPL-3
URL:	https://github.com/JavierDeLaHoz/LDAShiny
NeedsCompilation:	no
Language:	en-US
CRAN checks:	LDAShiny results

Documentation:

Reference manual:	LDAShiny.html , LDAShiny.pdf
Vignettes:	Introduction to LDAShiny: Bibliometric Topic Modeling (source, R code)

Downloads:

Package source:	LDAShiny_1.0.0.tar.gz
Windows binaries:	r-devel: not available, r-release: LDAShiny_1.0.0.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): LDAShiny_1.0.0.tgz, r-oldrel (arm64): LDAShiny_1.0.0.tgz, r-release (x86_64): LDAShiny_1.0.0.tgz, r-oldrel (x86_64): LDAShiny_1.0.0.tgz
Old sources:	LDAShiny archive

Linking:

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