Package: doc2concrete 0.6.0

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.

Authors:Mike Yeomans

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Bug tracker:https://github.com/myeomans/doc2concrete/issues

On CRAN:

2 exports 10 stars 1.77 score 61 dependencies 1 dependents 16 scripts 350 downloads

Last updated 8 months agofrom:db47b81370. Checks:OK: 7. Indexed: yes.

Exports:doc2concretengramTokens

Dependencies:BHclicodetoolscpp11data.tabledigestdplyrdttenglishfansifastmatchforeachgenericsglmnetgluehunspellISOcodesiteratorsjsonlitekoRpuskoRpus.lang.enlatticelexiconlifecyclemagrittrMatrixmgsubNLPpillarpkgconfigpurrrqdapRegexquantedaR6RcppRcppArmadilloRcppEigenrlangshapeslamSnowballCstopwordsstringistringrsurvivalsyllysylly.ensyuzhettextcleantextshapetextstemtibbletidyrtidyselecttmutf8vctrswithrxml2yamlzoo