Jack Carlisle, Mohammed Karaki, Cristian Rodriguez
We use tools in NLP, specifically sentiment analysis, to understand the 2019 Australian election. We train five models that predict sentiment on a Twitter dataset unrelated to the election. Using the highest quality model we label Australian Election tweets as positive or negative. Using our prediction of sentiment we succeed in predicting the political affiliation of a Twitter user based on how their sentiment shifts over time as the election results become available.