4.6 Article

stm: An R Package for Structural Topic Models

Journal

JOURNAL OF STATISTICAL SOFTWARE
Volume 91, Issue 2, Pages 1-40

Publisher

JOURNAL STATISTICAL SOFTWARE
DOI: 10.18637/jss.v091.i02

Keywords

structural topic model; text analysis; LDA; stm; R

Funding

  1. Spencer Foundation's New Civics initiative
  2. Hewlett Foundation
  3. National Science Foundation grant under the Resource Implementations for Data Intensive Research program
  4. Princeton's Center for Statistics and Machine Learning
  5. Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health [P2CHD047879]

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This paper demonstrates how to use the R package stm for structural topic modeling. 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.

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