Stock Market Prediction Using Yahoo finance and Twitter Polarity

Predicting the stock market is one of the intriguing and real life problem statements. In the current virtual world, social media like Twitter is the perfect representation of public opinion. Using the information available on these platforms, we can create very genuine and helpful insights about stocks. This paper explains different methods of interactively learning the complex market and its trends. We have used three different models for this paper which are Support Vector Regression, Long Short Term Memory and Random Forest and have also performed sentiment analysis on tweets related to Apple stock and compared the final results with Amazon and Tesla results. The model with the least error is the ideal and the most preferred method for prediction. We have combined Twitter's polarity data with Yahoo Finance's stock data for an efficient input. The results have given us a clear polarity view, both a statistical, and a graphical view.