Prediction of Stock Market Shift using Sentiment Analysis of Twitter Feeds, Clustering and Ranking

The stock market is fluctuating constantly. The rise and fall in stock prices are seemingly random. However, this is not so. Even a minute happening in the company can have a huge effect on the stock price. As each investor buys and sells the stock, the price rises and falls depending on the sale and purchase, the demand and supply. Whether or not an investor buys a particular company's stock is based on his knowledge and impression of the company. The latter is what we will employ to decide whether or not to buy a certain company's stock at the current price. There are 6 accepted discrete moods. Millions of people tweet every second. A fairly accurate prediction and analysis of the tweet's underlying mood can be made using sentiment analysis. Each word has a certain grammatical signature that tells us which mood it belongs to. Depending on what the users are feeling about a company as they tweet about it this engine will decide whether or not one should buy stocks of that company. This paper describes how to map this mood with market sentiment and in turn with prediction of rise/fall of stock prices.