sts - Estimation of the Structural Topic and Sentiment-Discourse Model
for Text Analysis
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 (2025)
<doi:10.1287/mnsc.2022.00261>.
