Students: Nicholas Bowen, Susan Liu, Cecelia Shuai, Jacky Chen
Link to performance sheet: https://docs.google.com/spreadsheets/d/1X-nTQbxYvv6v8T3O3YmgESnnZsjOA2H-/edit?usp=sharing&ouid=114424417712474397416&rtpof=true&sd=true
Description: Stocks are a particularly volatile that are influenced by many different interacting things including public opinion, economics, and institutional factors. We want to investigate the linkage between public opinion and stock price to see whether public opinion has predictive power in regards to stock prices, specifically in regards to twitter tweets and Tesla stock price. We propose building a pipeline that will take in twitter tweets and use sentiment analysis to classify tweets as positive or negative. The output of this section will then be used to build a dataset that will be an input to a classification task that will predict whether a stock is likely to increase or decrease within the next few days.