textTopicsWordcloud

This function create word clouds and topic fugures

Link R with Transformers from Hugging Face to transform text variables to word embeddings; where the word embeddings are used to statistically test the mean difference between set of texts, compute semantic similarity scores between texts, predict numerical variables, and visual statistically significant words according to various dimensions etc. For more information see <https://www.r-text.org>.

Oscar Kjell

text

Analyses of Text using Transformers Models from HuggingFace,
Natural Language Processing and Machine Learning

Salvatore Giorgi

Andrew Schwartz

textTopicsWordcloud function

<dl><dt>model</dt>
<dd>(list) A trained topics model. For examples from topicsModel(). Should be NULL if plotting ngrams.</dd>
<dt>ngrams</dt>
<dd>(list) The output from the the topicsGram() function . Should be NULL if plotting topics.</dd>
<dt>test</dt>
<dd>(list) The test results; if plotting according to dimension(s) include the object from topicsTest() function.</dd>
<dt>seed</dt>
<dd>(integer) The seed to set for reproducibility; need to be the same seed number as in in</dd>
<dt>...</dt>
<dd>Parameters from the topicsPlot() function in the topics package.</dd></dl>

Arguments

Plot word clouds — textTopicsWordcloud

<dl>

<dt>model</dt>
<dd>(list) A trained topics model. For examples from topicsModel(). Should be NULL if plotting ngrams.</dd>


<dt>ngrams</dt>
<dd>(list) The output from the the topicsGram() function . Should be NULL if plotting topics.</dd>


<dt>test</dt>
<dd>(list) The test results; if plotting according to dimension(s) include the object from topicsTest() function.</dd>


<dt>seed</dt>
<dd>(integer) The seed to set for reproducibility; need to be the same seed number as in in</dd>


<dt>...</dt>
<dd>Parameters from the topicsPlot() function in the topics package.</dd>

</dl>

textTopicsWordcloud: Plot word clouds

Description

Usage

Value

Arguments