If Amazon can predict what books we want to read, Netflix can predict what movies we want to watch, and Google, if you are feeling lucky, can predict what we are looking for, then it wouldnt be farfetched to say that Twitter can predict what stocks we should buy. The prediction of stock trends based on this kind of data analysis have been a hot topic for some time now, because of the growth of social media and our technological advances in analyzing large amounts of data. With the development of various computing methods there have been studies [demonstrating that] computing techniques outperform conventional models in most cases. The conventional investor, a long-term, rational person who picks stocks based on a companys history, board team, and projected performance, is now a bit of an anachronism. It is still true that past performance does not indicate future gains but we do know that individual stocks, and the market as a whole, are not 100% unpredictable. Cliff Asness provides some insight that the market is generally efficient, but not entirely so and that both market efficiency and human behavior move markets. In particular, it is possible that new information is not incorporated into the stock price instantaneously. One source of such information may be tweets. We ask whether tweets about companies and their stock tickers, contain information that is not yet calculated into the price of the stock.