_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-doc2concrete 0.6.0
Propagated dependencies: r-tm@0.7-14 r-textstem@0.1.4 r-stringr@1.5.1 r-stringi@1.8.4 r-snowballc@0.7.1 r-quanteda@4.1.0 r-glmnet@4.1-8 r-english@1.2-6
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=doc2concrete
Licenses: Expat
Synopsis: Measuring Concreteness in Natural Language
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.

Total results: 1