We did sentiment analysis on news stories of a particular stock and then used Microsoft Azure to find out how they affected the stock price.
We wrote a Python script to scrape news articles from Reuters. We scraped news articles for the AAPL, GOOG and MSFT stock for each day in the past ten years. We combined all the news articles on a particular day and used TextBlob to do sentiment anaylsis on it.
We also used Pandas to fetch stock price data from Yahoo Finance for the past ten years. We then combined the stock price data with the sentiment of the news articles. We then calculated the daily returns for each of the stock. So for each stock we had the daily return and the sentiment (polarity and subjectivity) for the past 10 years.
We used Azure ML to build a Neural Network to predict the return of a stock by looking at the sentiment of the news for the stock for the current day.