*Optional: Create a virtual environment.

To run the notebooks:

1. git lfs clone git@github.com:b-d-johnson/banned_books.git
2. cd banned_books
3. pip install -r requirements.txt or pip3 install -r requirements.txt
4. jupyter notebook

Datasets

• The list of banned books (provided by the ALA and PEN) may be found in data/pen_dataset.csv.
• The scraped Amazon.com reviews on the banned books may be found in data/scraped_amz_reviews.csv.


Supervised Sentiment Analysis

To run the best performing supervised sentiment analysis model (Logistic Regression):

jupyter notebook supervised_sentiment_analysis/supervised_logistic_regression_full.ipynb

To run a full search for the best performing supervised sentiment analysis model:

jupyter notebook supervised_sentiment_analysis/supervised_model_selection_random_search_cv.ipynb

Unsupervised Topic Modeling

To run the LDA topic modelling analysis (before) the first book ban:

jupyter notebook unsupervised_topic_modeling/2_LDA_Topics_Before_Book_Ban.ipynb

To run the LDA topic modelling analysis (after) the first book ban:

jupyter notebook unsupervised_topic_modeling/3_LDA_Topics_After_Book_Ban.ipynb

EDA of Banned Books Dataset

To run some exploratory data analysis:

jupyter notebook Appendix_EDA.ipynb

To Re-Run the Amazon.com customer review scraper on the banned books list:

jupyter notebook amazon_review_scraper.ipynb