Package: LDAShiny 1.1.0

Javier De La Hoz-M

LDAShiny: Shiny Application for Topic Modeling of Scientific Literature

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>.

Authors:Javier De La Hoz-M [aut, cre], Maria Camila Samper Meza [aut], Alexander Armando Bustamante Martínez [aut]

LDAShiny_1.1.0.tar.gz
LDAShiny_1.1.0.zip(r-4.7-any)LDAShiny_1.1.0.zip(r-4.6-any)
LDAShiny_1.1.0.tar.gz(r-4.7-any)LDAShiny_1.1.0.tar.gz(r-4.6-any)
LDAShiny_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
LDAShiny/json (API)

# Install 'LDAShiny' in R:
install.packages('LDAShiny', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jdelahoz-m/ldashiny/issues

On CRAN:

Conda:

2.60 score 7 scripts 289 downloads 16 exports 118 dependencies

Last updated from:89723b2764. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK213
source / vignettesOK259
linux-releaseOK200
windows-develOK151
windows-releaseOK168
wasm-releaseOK128

Exports:mod_about_servermod_about_uimod_import_bibliometrics_servermod_import_bibliometrics_uimod_inference_uimod_lda_trainmod_lda_train_servermod_lda_train_uimod_preprocess_servermod_preprocess_uimod_sensitivitymod_sensitivity_servermod_sensitivity_uimod_trend_servermod_trend_uirun_LDAShiny

Dependencies:attemptaudiobackportsbase64encbeeprBHbroombslibcachemcellrangerclicodetoolscolourpickercommonmarkconfigcpp11crayoncrosstalkdata.tabledigestdplyrDTevaluatefarverfastmapfastmatchfloatfontawesomefsgenericsggplot2ggrepelgluegolemgtablegtoolshighrhmshtmltoolshtmlwidgetshttpuvigraphisobandISOcodesjquerylibjsonliteknitrlabelinglaterlatticelazyevalLDAvislgrlifecyclemagrittrMatrixMatrixExtramemoisemimeminiUImlapiNLPopenxlsxotelpillarpkgconfigprettyunitsprogresspromisesproxypurrrquantedaR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppProgressreadxlrematchRhpcBLASctlRJSONIOrlangrmarkdownrsparseRSpectraS7sassscalesshinyshinybusyshinydashboardshinyjsshinyWidgetsslamSnowballCsourcetoolsstopwordsstringistringrtext2vectextmineRtibbletidyrtidyselecttinytextmutf8vctrsviridisLitewithrwordcloudxfunxml2xtableyamlzip

LDAShiny: flujo de trabajo guiado para modelado de tópicos
Introducción | Instalación e inicio | Cómo se conectan los módulos | Paso 0. Acerca de (About) | Paso 1. Importación de datos (Import Data) | Limpieza PRISMA | Exploración del corpus | Paso 1b. Análisis geográfico y de revistas (Geographic & Journal Analysis) | Pestaña 1 — Country & Journal | Pestaña 2 — Country Map | Pestaña 3 — Collaboration Network | Paso 2. Preprocesamiento del texto (Preprocess) | Paso 3. Elección del número de tópicos (LDA Inference) | Paso 4. Estabilidad y sensibilidad (Stability & Sensitivity) | Configuración | Criterios de la puntuación compuesta | Resultados | Paso 5. Entrenamiento del modelo final (Final LDA Model) | Parámetros | Numeración consistente de tópicos | LDAvis | El modelo descargado | Paso 6. Tendencias temporales (Topic Trends) | Opciones | Clasificación | Archivos generados por la aplicación | Consejos y solución de problemas | Cómo citar | Referencias
Rendered fromGuia_LDAShiny.Rmdusingknitr::rmarkdown

Last update: 2026-10-30
Started: 2026-10-30

LDAShiny: a complete guided workflow for topic modeling
Introduction | Installation and launch | How the modules connect | Step 0. About | Step 1. Importing data (Import Data) | PRISMA cleaning | Exploring the corpus | Step 1b. Geographic and journal analysis (Geographic & Journal Analysis) | Tab 1 — Country & Journal | Tab 2 — Country Map | Tab 3 — Collaboration Network | Step 2. Preprocessing the text (Preprocess) | Step 3. Choosing the number of topics (LDA Inference) | Step 4. Stability and sensitivity (Stability & Sensitivity) | Configuration | Composite score criteria | Results | Step 5. Training the final model (Final LDA Model) | Parameters | Consistent topic numbering | LDAvis | The downloaded model | Step 6. Temporal trends (Topic Trends) | Options | Classification | Files generated by the application | Tips and troubleshooting | How to cite | References
Rendered fromGuided_LDAShiny.Rmdusingknitr::rmarkdown

Last update: 2026-10-30
Started: 2026-10-30

Readme and manuals

Help Manual

Help pageTopics
About Servermod_about_server
About UImod_about_ui
Import Bibliometrics Servermod_import_bibliometrics_server
Import Bibliometrics UImod_import_bibliometrics_ui
LDA Inference Modulemod_inference mod_inference_server mod_inference_ui themes_gg
Final LDA Model Training Modulemod_lda_train mod_lda_train_server mod_lda_train_ui
Text Preprocessing Module for LDAShinymod_preprocess mod_preprocess_server mod_preprocess_ui
Stability & Sensitivity Analysis Modulemod_sensitivity mod_sensitivity_server mod_sensitivity_ui
Topic Trend Analysis Modulemod_trend mod_trend_server mod_trend_ui
Run the LDAShiny Applicationrun_LDAShiny