Sentiment-Analysis-Airline-Tweets

The research goal was to build machine learning models that classify tweets about airlines into the categories “positive” or “negative.” To do this, we created a corpus of common words from tweets about airlines and used Spark and Python to analyze the data. While constructing our models, we explored the data to learn about trends between variables, discover commonly used words in airline tweets, and learn which terms are important for determining sentiment.