  The stock market is a network which provides a platform for almost all major
economic transactions. While investing in the stock market is a good idea,
investing in individual stocks may not be, especially for the casual investor.
Smart stock-picking requires in-depth research and plenty of dedication.
Predicting this stock value offers enormous arbitrage profit opportunities.
This attractiveness of finding a solution has prompted researchers to find a
way past problems like volatility, seasonality, and dependence on time. This
paper surveys recent literature in the domain of natural language processing
and machine learning techniques used to predict stock market movements. The
main contributions of this paper include the sophisticated categorizations of
many recent articles and the illustration of the recent trends of research in
stock market prediction and its related areas.
