Shiny Application for Topic Modeling of Scientific Literature R package LDAShiny version 1.1.0 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>. Software 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) Javier De La Hoz-M <jdelahoz@unimagdalena.edu.co> Comprehensive R Archive Network (CRAN) Javier De La Hoz-M [aut, cre] (ORCID: <https://orcid.org/0000-0001-7779-0803>), Maria Camila Samper Meza [aut] (ORCID: <https://orcid.org/0009-0005-9235-8732>), Alexander Armando Bustamante Martínez [aut] (ORCID: <https://orcid.org/0000-0003-4422-018X>) GPL-3 2026-10-30 application/tgz https://CRAN.R-project.org/package=LDAShiny doi:10.32614/CRAN.package.LDAShiny en-US