Measuring Concreteness in Natural Language

Models for detecting concreteness in natural language. This package is built in support of Yeomans (2020) , 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) ) as well as two pre-trained models for the feedback and plan-making domains.


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install.packages("doc2concrete")

0.4.6 by Mike Yeomans, 4 months ago


Browse source code at https://github.com/cran/doc2concrete


Authors: Mike Yeomans


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports tm, quanteda, ggplot2, parallel, glmnet, stringr, dplyr, english, textstem, SnowballC, textclean

Suggests knitr, rmarkdown, testthat


See at CRAN