Keyword Assisted Topic Model

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 (2020) .


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Reference manual

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install.packages("keyATM")

0.3.1 by Shusei Eshima, 9 days ago


https://keyatm.github.io/keyATM/


Report a bug at https://github.com/keyATM/keyATM/issues


Browse source code at https://github.com/cran/keyATM


Authors: Shusei Eshima [aut, cre] , Tomoya Sasaki [aut] , William Lowe [ctb] , Kosuke Imai [aut] , Chung-hong Chan [ctb] , Romain Fran├žois [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, dplyr, fastmap, ggplot2, ggrepel, magrittr, Matrix, parallel, purrr, quanteda, rlang, stats, stringr, tibble, tidyr

Suggests readtext, testthat

Linking to Rcpp, RcppEigen, RcppProgress

System requirements: C++11


See at CRAN