This function takes the output from scrape_reviews, preprocesses the data, performs topic modeling, and prints the results.
Value
A list containing the following elements:
model
: The fitted LDA model object.filtered_reviews
: The preprocessed and filtered reviews data frame.
Examples
# \donttest{
# 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)
#> Total book IDs to process: 3
#> 2024-09-03 16:16:23.379464 scrape_goodreads_reviews: Completed! All book reviews extracted
#> Scraping run time = 7.55955243110657
#> Total books processed: 3
# Model topics
topic_results <- model_topics(reviews, num_topics = 2, num_terms = 5, english_only = TRUE)
#> Topic 1:
#> fuck, hamlet, just, like, get
#>
#> Topic 2:
#> love, jane, book, read, rochest
#>
# Print model summary
print(topic_results$model)
#> A LDA_Gibbs topic model with 2 topics.
# Clean up: remove the temporary file
file.remove(temp_file)
#> [1] TRUE
# }