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Models for detecting concreteness in natural language. This package is built in support of Yeomans (2021) <doi:10.1016/j.obhdp.2020.10.008>, which reviews linguistic models of concreteness in several domains. Here, we provide an implementation of the best-performing domain-general model (from Brysbaert et al., (2014) <doi:10.3758/s13428-013-0403-5>) as well as two pre-trained models for the feedback and plan-making domains.
Version: | 0.6.0 |
Depends: | R (≥ 3.5.0) |
Imports: | tm, quanteda, parallel, glmnet, stringr, english, textstem, SnowballC, stringi |
Suggests: | knitr, rmarkdown, testthat |
Published: | 2024-01-23 |
DOI: | 10.32614/CRAN.package.doc2concrete |
Author: | Mike Yeomans |
Maintainer: | Mike Yeomans <mk.yeomans at gmail.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | doc2concrete results |
Reference manual: | doc2concrete.pdf |
Vignettes: |
doc2concrete |
Package source: | doc2concrete_0.6.0.tar.gz |
Windows binaries: | r-devel: doc2concrete_0.6.0.zip, r-release: doc2concrete_0.6.0.zip, r-oldrel: doc2concrete_0.6.0.zip |
macOS binaries: | r-release (arm64): doc2concrete_0.6.0.tgz, r-oldrel (arm64): doc2concrete_0.6.0.tgz, r-release (x86_64): doc2concrete_0.6.0.tgz, r-oldrel (x86_64): doc2concrete_0.6.0.tgz |
Old sources: | doc2concrete archive |
Reverse imports: | DICEM |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.