Journal
JOURNAL OF STATISTICAL SOFTWARE
Volume 91, Issue 2, Pages 1-40Publisher
JOURNAL STATISTICAL SOFTWARE
DOI: 10.18637/jss.v091.i02
Keywords
structural topic model; text analysis; LDA; stm; R
Funding
- Spencer Foundation's New Civics initiative
- Hewlett Foundation
- National Science Foundation grant under the Resource Implementations for Data Intensive Research program
- Princeton's Center for Statistics and Machine Learning
- 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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