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
Insights
Last 30 days
This package has been downloaded 546 times in the last 30 days. More downloads than an obscure whitepaper, but not enough to bring down any servers. A solid effort! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.
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Last 365 days
This package has been downloaded 6,356 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Apr 25, 2024 with 61 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports20 packages
- Suggests2 packages
- Linking To3 packages
- Reverse Suggests3 packages