doc2concrete: Measuring Concreteness in Natural Language
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 + fileLICENSE |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | doc2concrete results |
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