topicdoc: Topic-Specific Diagnostics for LDA and CTM Topic Models

Calculates topic-specific diagnostics (e.g. mean token length, exclusivity) for Latent Dirichlet Allocation and Correlated Topic Models fit using the 'topicmodels' package. For more details, see Chapter 12 in Airoldi et al. (2014, ISBN:9781466504080), pp 262-272 Mimno et al. (2011, ISBN:9781937284114), and Bischof et al. (2014) <doi:10.48550/arXiv.1206.4631>.

Version:	0.1.1
Depends:	R (≥ 3.5.0)
Imports:	slam, topicmodels
Suggests:	knitr, rmarkdown, stm, testthat (≥ 2.1.0)
Published:	2022-07-17
DOI:	10.32614/CRAN.package.topicdoc
Author:	Doug Friedman [aut, cre]
Maintainer:	Doug Friedman <doug.nhp at gmail.com>
BugReports:	https://github.com/doug-friedman/topicdoc/issues
License:	MIT + file LICENSE
URL:	https://github.com/doug-friedman/topicdoc
NeedsCompilation:	no
Materials:	README, NEWS
In views:	NaturalLanguageProcessing
CRAN checks:	topicdoc results

Documentation:

Reference manual:	topicdoc.html , topicdoc.pdf
Vignettes:	Basic usage (source, R code)

Downloads:

Package source:	topicdoc_0.1.1.tar.gz
Windows binaries:	r-devel: topicdoc_0.1.1.zip, r-release: topicdoc_0.1.1.zip, r-oldrel: topicdoc_0.1.1.zip
macOS binaries:	r-release (arm64): topicdoc_0.1.1.tgz, r-oldrel (arm64): topicdoc_0.1.1.tgz, r-release (x86_64): topicdoc_0.1.1.tgz, r-oldrel (x86_64): topicdoc_0.1.1.tgz
Old sources:	topicdoc archive

Reverse dependencies:

Reverse suggests:

mia

Linking:

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