SENTIMENTAL ANALYSIS OF STOCK MARKET VOLATILITY BY MACHINE LEARNING

Abstract: Stock Market Prediction is a platform where an enormous amount of data exists and constantly needs to be scrutinized. Traditional stock market prediction models are based on analysis of historical market data. Stock Market Prediction on the basis of public sentiments based on social media – an intriguing field of research. Positive tweets and news in social media encourage people to invest in the stocks of the company, thereby increasing the stock price of the company. Data sets are so large that it is difficult to analyze them using traditional data processing applications. We can extract the useful information to an understandable structure using machine learning algorithms, and Sentiment Analysis as the approaches, we implement and simulate a brokerage system and analyze the stock market. Key Words: Stock Market, Sentimental analysis, TextBlob, Machine Learning Algorithms, Natural language Processing, WebScraping