sentopics: Tools for Joint Sentiment and Topic Analysis of Textual Data

A framework that joins topic modeling and sentiment analysis of textual data. The package implements a fast Gibbs sampling estimation of Latent Dirichlet Allocation (Griffiths and Steyvers (2004) <doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He, Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of helpers and visualizations to analyze the result of topic modeling. The framework also allows enriching topic models with dates and externally computed sentiment measures. A flexible aggregation scheme enables the creation of time series of sentiment or topical proportions from the enriched topic models. Moreover, a novel method jointly aggregates topic proportions and sentiment measures to derive time series of topical sentiment.

Version: 0.7.6
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.4.6), methods, generics, quanteda (≥ 3.2.0), data.table (≥ 1.13.6), RcppHungarian
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: ggplot2, ggridges, plotly, RColorBrewer, xts, zoo, future, future.apply, progressr, progress, testthat, covr, stm, lda, topicmodels, seededlda (≥ 1.4.0), keyATM, LDAvis, servr, textcat, stringr, sentometrics, spacyr, knitr, rmarkdown, webshot
Published: 2025-10-15
DOI: 10.32614/CRAN.package.sentopics
Author: Olivier Delmarcelle ORCID iD [aut, cre], Samuel Borms ORCID iD [ctb], Chengua Lin [cph] (Original JST implementation), Yulan He [cph] (Original JST implementation), Jose Bernardo [cph] (Original JST implementation), David Robinson [cph] (Implementation of reorder_within()), Julia Silge ORCID iD [cph] (Implementation of reorder_within())
Maintainer: Olivier Delmarcelle <delmarcelle.olivier at gmail.com>
BugReports: https://github.com/odelmarcelle/sentopics/issues
License: GPL (≥ 3)
URL: https://github.com/odelmarcelle/sentopics
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: sentopics results

Documentation:

Reference manual: sentopics.html , sentopics.pdf
Vignettes: Basic usage (source, R code)
Topical time series (source, R code)

Downloads:

Package source: sentopics_0.7.6.tar.gz
Windows binaries: r-devel: sentopics_0.7.6.zip, r-release: sentopics_0.7.6.zip, r-oldrel: sentopics_0.7.6.zip
macOS binaries: r-release (arm64): sentopics_0.7.6.tgz, r-oldrel (arm64): sentopics_0.7.6.tgz, r-release (x86_64): sentopics_0.7.6.tgz, r-oldrel (x86_64): sentopics_0.7.6.tgz
Old sources: sentopics archive

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