Latent Dirichlet Allocation Using 'tidyverse' Conventions R package tidylda version 0.0.7 Implements an algorithm for Latent Dirichlet Allocation (LDA), Blei et at. (2003) <https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf>, using style conventions from the 'tidyverse', Wickham et al. (2019)<doi:10.21105/joss.01686>, and 'tidymodels', Kuhn et al.<https://tidymodels.github.io/model-implementation-principles/>. Fitting is done via collapsed Gibbs sampling. Also implements several novel features for LDA such as guided models and transfer learning. Software Depends: R (>= 3.5.0) Imports: dplyr, generics, gtools, Matrix, methods, mvrsquared (>= 0.1.0), Rcpp (>= 1.0.2), rlang, stats, stringr, tibble, tidyr, tidytext LinkingTo: Rcpp, RcppArmadillo, RcppProgress, RcppThread Suggests: ggplot2, knitr, parallel, quanteda, testthat, tm, slam, spelling, covr, rmarkdown Tommy Jones <jones.thos.w@gmail.com> Comprehensive R Archive Network (CRAN) Tommy Jones [aut, cre] (ORCID: <https://orcid.org/0000-0001-6457-2452>), Brendan Knapp [ctb] (ORCID: <https://orcid.org/0000-0003-3284-4972>), Barum Park [ctb] MIT + file LICENSE (https://CRAN.R-project.org/package=tidylda/LICENSE) 2025-11-14 application/tgz https://CRAN.R-project.org/package=tidylda doi:10.32614/CRAN.package.tidylda en-US