model_topics: Analyze topics in Goodreads reviews

In Goodreader: Scrape and Analyze 'Goodreads' Book Data

Analyze topics in Goodreads reviews

Description

This function takes the output from scrape_reviews, preprocesses the data, performs topic modeling, and prints the results.

Usage

model_topics(reviews, num_topics = 3, num_terms = 10, english_only = TRUE)

Arguments

reviews	A data frame containing the scraped reviews
num_topics	The number of topics to extract
num_terms	The number of top terms to display for each topic
english_only	A logical value indicating whether to filter out non-English reviews. Default is FALSE.

Value

A list containing the following elements:

• model: The fitted LDA model object.

• filtered_reviews: The preprocessed and 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)

# Model topics
topic_results <- model_topics(reviews, num_topics = 2, num_terms = 5, english_only = TRUE)

# Print model summary
print(topic_results$model)

# Clean up: remove the temporary file
file.remove(temp_file)

Goodreader documentation built on Oct. 30, 2024, 9:11 a.m.