keyATM
Keyword Assisted Topic Models
Fits keyword assisted topic models (keyATM) using collapsed Gibbs samplers. The keyATM combines the latent dirichlet allocation (LDA) models with a small number of keywords selected by researchers in order to improve the interpretability and topic classification of the LDA. The keyATM can also incorporate covariates and directly model time trends. The keyATM is proposed in Eshima, Imai, and Sasaki (2024) doi:10.1111/ajps.12779.
- Version0.5.2
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- keyATM citation info
- Last release04/24/2024
Documentation
Team
Shusei Eshima
Kosuke Imai
Chung-hong Chan
Romain François
Tomoya Sasaki
Show author detailsRolesAuthorWilliam Lowe
Show author detailsRolesContributorSeo-young Silvia Kim
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- Imports20 packages
- Suggests2 packages
- Linking To3 packages
- Reverse Suggests3 packages