[R Course] Structural Topic Model: stm R package

R Courses NLP

Flexibly estimate a topic model that includes document-level metadata.

Thierry Warin https://warin.ca/aboutme.html (HEC Montréal and CIRANO (Canada))https://www.hec.ca/en/profs/thierry.warin.html
03-23-2020

Course objectives

This course demonstrates how to use the Structural Topic Model stm R package. The Structural Topic Model allows researchers to flexibly estimate a topic model that includes document-level metadata. Estimation is accomplished through a fast variational approximation. The stm package provides many useful features, including rich ways to explore topics, estimate uncertainty, and visualize quantities of interest.

Course plan

1. The Structural Topic Model

Heuristic description of selected stm package features.

2. Ingest

Reading and processing text data.

3. Prepare

Associating text with metadata.

4. Estimate

Estimating the structural topic model.

5. Evaluate

Model selection and search.

6. Understand

Interpreting the STM by plotting and inspecting results.

7. Visualize

Presenting STM results.

8. Extensions

Changing basic estimation defaults.

Altering the prior structure.



ACCESS TO THE COURSE



Citation

For attribution, please cite this work as

Warin (2020, March 23). Thierry Warin, PhD: [R Course] Structural Topic Model: stm R package. Retrieved from https://warin.ca/posts/rcourse-structural-topic-model/

BibTeX citation

@misc{warin2020[r,
  author = {Warin, Thierry},
  title = {Thierry Warin, PhD: [R Course] Structural Topic Model: stm R package},
  url = {https://warin.ca/posts/rcourse-structural-topic-model/},
  year = {2020}
}