text_clean

This file contains helper functions for text processing and cleaning used in the 'sumup' package.
The functions provide capabilities for text correction, cleaning, dataset preparation, and handling abbreviation replacements.
Cleans narrative text columns (<code>sterk</code>, <code>verbeter</code>, <code>feedback</code>) in a dataset.

Combine topic modeling and sentiment analysis to identify individual students' gaps, and highlight their strengths and weaknesses across predefined competency domains and professional activities.

Joyce Moonen - van Loon

sumup

Utilizing Automated Text Analysis to Support Interpretation of
Narrative Feedback

text_clean function

<dl><dt>data</dt>
<dd>A data.table or data.frame containing text data.</dd>
<dt>corrections_file</dt>
<dd>Path to a CSV file containing typo corrections.</dd></dl>

Arguments

Joyce M.W. Moonen - van Loon
This file defines several functions:<ul>
<li><code>text_clean()</code>: Cleans multiple columns in a dataset.</li>
<li><code>correct_text()</code>: Applies typo corrections using a predefined correction list.</li>
<li><code>clean_text()</code>: Cleans and formats input text, handling HTML tags, spacing, punctuation, and typos.</li>
<li><code>get_corrections()</code>: Reads a correction file and processes typo replacements.</li>
<li><code>create_dataset_narratives()</code>: Prepares a dataset by restructuring and normalizing its textual content.</li>
<li><code>replace_abbr()</code>: Corrects abbreviations.</li>
</ul>

Author

Text Cleaning and Processing Functions — text_clean

<dl>

<dt>data</dt>
<dd>A data.table or data.frame containing text data.</dd>


<dt>corrections_file</dt>
<dd>Path to a CSV file containing typo corrections.</dd>

</dl>

text_clean: Text Cleaning and Processing Functions

Description

Usage

Value

Arguments

Author