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sentopics  

Tools for Joint Sentiment and Topic Analysis of Textual Data
View on CRAN: Click here


Download and install sentopics package within the R console
Install from CRAN:
install.packages("sentopics")

Install from Github:
library("remotes")
install_github("cran/sentopics")

Install by package version:
library("remotes")
install_version("sentopics", "0.7.6")



Attach the package and use:
library("sentopics")
Maintained by
Olivier Delmarcelle
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-03-10
Latest Update: 2024-09-20
Description:
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.
How to cite:
Olivier Delmarcelle (2022). sentopics: Tools for Joint Sentiment and Topic Analysis of Textual Data. R package version 0.7.6, https://cran.r-project.org/web/packages/sentopics. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.6.1 (2022-03-10 09:00), 0.6.2 (2022-03-15 14:50), 0.7.0 (2022-05-09 09:10), 0.7.1 (2022-05-18 15:20), 0.7.2 (2023-05-28 11:50), 0.7.3 (2024-04-18 15:12), 0.7.4 (2024-09-20 14:20), 0.7.5 (2025-09-29 22:50)
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Complete documentation for sentopics
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