Package: doc2concrete
Type: Package
Title: Measuring Concreteness in Natural Language
Version: 0.5.4
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 (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.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: tm, quanteda, parallel, glmnet, stringr, english, textstem,
        SnowballC, stringi
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-05-17 20:14:16 UTC; myeomans
Repository: CRAN
Date/Publication: 2021-05-17 20:40:02 UTC
Built: R 4.0.5; ; 2022-04-21 14:55:21 UTC; windows
