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sts  

Estimation of the Structural Topic and Sentiment-Discourse Model for Text Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("sts", "1.4")



Attach the package and use:
library("sts")
Maintained by
Shawn Mankad
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-09-17
Latest Update: 2025-01-25
Description:
The Structural Topic and Sentiment-Discourse (STS) model allows researchers to estimate topic models with document-level metadata that determines both topic prevalence and sentiment-discourse. The sentiment-discourse is modeled as a document-level latent variable for each topic that modulates the word frequency within a topic. These latent topic sentiment-discourse variables are controlled by the document-level metadata. The STS model can be useful for regression analysis with text data in addition to topic modeling’s traditional use of descriptive analysis. The method was developed in Li and Mankad (2024) <doi:10.2139/ssrn.4020651>.
How to cite:
Shawn Mankad (2024). sts: Estimation of the Structural Topic and Sentiment-Discourse Model for Text Analysis. R package version 1.4, https://cran.r-project.org/web/packages/sts. Accessed 12 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:10), 1.0 (2024-09-17 13:50), 1.1 (2024-11-06 17:10), 1.2 (2024-11-25 17:00), 1.3 (2025-01-17 19:30)
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Complete documentation for sts
Functions, R codes and Examples using the sts R package
Full sts package functions and examples
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