SXSW Conference Sentiment Analysis

Overview

An analysis and natural language processing of thousands of tweets is completed to predict sentiments during SXSW and provide insights to brands and products at the conference.

Though the extra trees classifier has the highest test accuracy, the Multinomial Naive Bayes model performs the best at classifying negative and positive sentiments.

Clustering analysis is performed to identify themes and topics that emerged, and recommendations are made accordingly.

Github: Repository