Package: doc2concrete
Type: Package
Title: Measuring Concreteness in Natural Language
Version: 0.4.6
Author: Mike Yeomans
Maintainer: Mike Yeomans <mk.yeomans@gmail.com>
Description: Models for detecting concreteness in natural language. This package is built in support of Yeomans (2020) <doi:10.17605/OSF.IO/DYZN6>, 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.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: tm, quanteda, ggplot2, parallel, glmnet, stringr, dplyr,
        english, textstem, SnowballC, textclean
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-06-13 17:28:37 UTC; myeomans
Repository: CRAN
Date/Publication: 2020-06-19 11:00:02 UTC
Built: R 4.1.0; ; 2020-08-03 15:04:32 UTC; windows
