This project was developed as part of an Artificial Intelligence course and focuses on applying Natural Language Processing (NLP) techniques to analyze sentiment in social media data. The goal of the project is to classify tweets related to the 2016 GOP Presidential Debate as positive, negative, or neutral using automated sentiment analysis techniques. By leveraging Python-based NLP tools, the project demonstrates how machine learning and AI methods can extract insights from large-scale textual datasets. This work was collaboratively developed by Alcaeus Andrea Conner and Garrett Drolet as part of coursework in Artificial Intelligence.