Poster for Suffolk STEAM Reception: https://drive.google.com/file/d/1x8KmIDuYnOsiTz4BbkfmHYZn4zxgJYpe/view?usp=sharing
Discovering which politicians are leaders or responders in conversations. Tweets by politicians were analyzed in Python over a 4 year span. To extract the top 3 topics for each candidate, tweets were grouped monthly using Pandas, and LDA models were built. The correlation of each topic was found with all others and is used to build a weighted graph using NetworkX.