preprocess_reviews {Goodreader} | R Documentation |
Preprocess review text for topic modeling
Description
This function preprocesses the review text by optionally filtering non-English reviews, removing punctuation, converting to lowercase, removing stopwords, and stemming.
Usage
preprocess_reviews(reviews, english_only = TRUE)
Arguments
reviews |
A data frame containing the scraped reviews |
english_only |
A logical value indicating whether to filter out non-English reviews. Default is TRUE |
Value
A list containing the following elements:
-
corpus
: The preprocessed corpus object. -
dtm
: The document-term matrix. -
filtered_reviews
: The filtered reviews data frame.
Examples
# Create a temporary file with sample book IDs
temp_file <- tempfile(fileext = ".txt")
writeLines(c("1420", "2767052", "10210"), temp_file)
# Scrape reviews
reviews <- scrape_reviews(temp_file, num_reviews = 5, use_parallel = FALSE)
# Preprocess the reviews
preprocessed <- preprocess_reviews(reviews, english_only = TRUE)
# Print the document-term matrix
print(preprocessed$dtm)
# Clean up: remove the temporary file
file.remove(temp_file)
[Package Goodreader version 0.1.1 Index]