R: Utilizing Automated Text Analysis to Support Interpretation of Narrative Feedback

# Utilizing Automated Text Analysis to Support Interpretation of Narrative Feedback

## Documentation for package ‘sumup’ version 1.0.3

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

append_stopwords | Append Stopwords
check_all_settings | Check all setting
check_setting | Check setting
clean_text | Clean Text
correct_text | Correct Text
create_dataset_narratives | Create Narratives Dataset
create_output | Create Output for Sum Up
default_stopwords | Load Stopwords
example_data | Example example_data
get_corrections | Load Corrections
get_polarity | Get Polarity from Grasp
lemmatize | Lemmatize Sentences Using a UDPipe Model
obtain_word_counts | Obtain Word Counts
replace_abbr | Replace Abbreviations
run_sumup | Run Sum Up
sentiment_analysis_sentimentr | Sentiment Analysis using sentimentr
set_default_settings | Settings functionality for package 'sumup'
text_clean | Text Cleaning and Processing Functions
tidy_text | Tidy and Split Narrative Text
topic_classification | Topic Classification for Narrative Data
topic_modeling | Topic Modeling with Latent Dirichlet Allocation (LDA)
update_educational_framework_settings | Update settings related to the educational framework
update_setting | Update setting