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Vampire-Reviews

In the Fall 2024 semester, I chose to analyze reviews of vampire movies for my final project in my DACSS 758: Text as Data course, taught by Dr. Rosemary Pang at UMass Amherst. I wanted to learn about which words are commonly used by movie critics to favorably describe vampire movies and develop models to predict whether a critic's vampire movie review is positive or negative.

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This repository contains 6 files:

  • README.md: this file
  • Vampire-Code.qmd: the R code used to build a Naive Bayes, Support Vector Machine, and Random Forest model to predict the freshness of vampire movie reviews
  • Vampire-Output.html: the rendered version of the QMD file, displaying the R code, interpretations, and output
  • vamp_reviews.csv: the data used to train the supervised learning models, obtained from Kaggle
  • new_vamp_reviews.csv: the data used to test the models, compiled from Rotten Tomatoes
  • Vampire-Poster.pdf: the digital poster summarizing the project's goals, methods, and major findings