Predicting Stock Price Using Sentimental Analysis Through Twitter Data

Abstract

Artificial intelligence and Machine learning methods in combination with data mining are used in multiple scenarios to solve many problems. These Machine learning methods and techniques have already proved to be effective, highly accurate and it saves a lot of time. In recent days, people have started investing in stocks and shares as it is a profitable option in order to increase one's income. If there are proper planning and good guidance there are chances of doubling the annual revenue from the returns we get from the stock market. But even in the present day's people think stock investments still remain a risky theory. Investment experts have very high income along with the ignorance of the general public with respect to the financial problems, some issues like these behave as barriers for many people to invest in stocks. The anxiety of losing the invested money also behaves as a barrier to the people. These facts are the motivation factors for applying the capacity of machine learning to do the prediction on the movements of stocks. The sentimental analysis is used on the tweets which are obtained by using the Twitter API. Such forecasts are of great use for stock investors so that they can take calculative decisions and invest in stocks that are profitable.