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sts

Estimation of the Structural Topic and Sentiment-Discourse Model for Text Analysis

v1.4 · Jan 25, 2025 · MIT + file LICENSE

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 Chen and Mankad (2024) <doi:10.1287/mnsc.2022.00261>.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Apr 22, 2026
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Dependency Network

Dependencies Reverse dependencies glmnet matrixStats slam foreach doParallel stm Matrix mvtnorm ggplot2 tm sts

Version History

6 tracked
new 1.4 Mar 10, 2026
updated 1.4 ← 1.3 diff Jan 25, 2025
updated 1.3 ← 1.2 diff Jan 16, 2025
updated 1.2 ← 1.1 diff Nov 24, 2024
updated 1.1 ← 1.0 diff Nov 5, 2024
new 1.0 Sep 16, 2024