Package: LDAShiny
Title: Interactive Topic Modeling and Bibliometric Analysis via Shiny
Version: 1.0.0
Authors@R: person("Javier", "De La Hoz-M",
    email = "jdelahoz@unimagdalena.edu.co",
    role  = c("aut", "cre"),
    comment = c(ORCID = "0000-0001-7779-0803"))
Description: 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.
License: GPL-3
URL: https://github.com/JavierDeLaHoz/LDAShiny
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
Encoding: UTF-8
RoxygenNote: 7.3.3
Config/testthat/edition: 3
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-07 17:54:36 UTC; Javier_de_la_Hoz
Author: Javier De La Hoz-M [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-7779-0803>)
Maintainer: Javier De La Hoz-M <jdelahoz@unimagdalena.edu.co>
Repository: CRAN
Date/Publication: 2026-06-08 06:50:14 UTC
Built: R 4.4.3; ; 2026-06-08 09:22:11 UTC; unix
