stemmer

internal

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.

Mike Yeomans

doc2concrete

Measuring Concreteness in Natural Language

stemmer function

<dl><dt>text</dt>
<dd>character vector of strings to clean.</dd>
<dt>wstem</dt>
<dd>character Which words should be stemmed? Defaults to "all".</dd>
<dt>language</dt>
<dd>Language for stemming. Default is "english".</dd></dl>

Arguments

Stemmer — stemmer

<dl>

<dt>text</dt>
<dd>character vector of strings to clean.</dd>


<dt>wstem</dt>
<dd>character Which words should be stemmed? Defaults to "all".</dd>


<dt>language</dt>
<dd>Language for stemming. Default is "english".</dd>

</dl>

stemmer: Stemmer

Description

Usage

Value

Arguments