A 'shiny' application that guides users through an exploratory review of scientific literature using Latent Dirichlet Allocation (LDA) topic modeling. It imports bibliometric records exported from databases such as 'Scopus' and 'Web of Science', performs text preprocessing, helps select the number of topics, fits the final model, and visualizes the results and the evolution of topics over time. The methodology is described in De la Hoz-M et al. (2021) <doi:10.3390/math9141671>.
| Version: | 1.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | beepr, broom, colourpicker, config, dplyr, DT, ggplot2, ggrepel, golem, igraph, jsonlite, LDAvis, Matrix, openxlsx, quanteda, RColorBrewer, readxl, scales, shiny, shinybusy, shinydashboard, shinyjs, shinyWidgets, slam, SnowballC, stopwords, textmineR, tibble, tidyr, tm, utils, wordcloud |
| Suggests: | knitr, plotly, purrr, readr, rmarkdown, shinyBS, testthat (≥ 3.0.0) |
| Published: | 2026-10-30 |
| DOI: | 10.32614/CRAN.package.LDAShiny |
| Author: | Javier De La Hoz-M
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| Maintainer: | Javier De La Hoz-M <jdelahoz at unimagdalena.edu.co> |
| BugReports: | https://github.com/jdelahoz-m/LDAShiny/issues |
| License: | GPL-3 |
| URL: | https://github.com/jdelahoz-m/LDAShiny |
| NeedsCompilation: | no |
| Language: | en-US |
| CRAN checks: | LDAShiny results |
| Reference manual: | LDAShiny.html , LDAShiny.pdf |
| Vignettes: |
Flujo de Trabajo Guiado para Análisis de Tópicos con LDAShiny (source, R code) LDAShiny: a complete guided workflow for topic modeling (source, R code) |
| Package source: | LDAShiny_1.1.0.tar.gz |
| Windows binaries: | r-devel: LDAShiny_1.0.0.zip, r-release: LDAShiny_1.0.0.zip, r-oldrel: LDAShiny_1.1.0.zip |
| macOS binaries: | r-release (arm64): LDAShiny_1.1.0.tgz, r-oldrel (arm64): LDAShiny_1.1.0.tgz, r-release (x86_64): LDAShiny_1.1.0.tgz, r-oldrel (x86_64): LDAShiny_1.1.0.tgz |
| Old sources: | LDAShiny archive |
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