Stock market sentiment analysis based on machine learning

Opinion mining is used as scrutiny of public opinions. The growth of social network has put onward the views of the general public on a larger scale and in an open manner. The comments, views and opinions act as deciding factors whether these are positive opinion or negative opinion. Guessing about the opinions' polarity is not a good idea, so, an intelligent system need to be introduced to categorize the views. Sentiment analysis thus emerged as a highlighted area in data mining. The opinions are judged on the basis of unsupervised and supervised learning. Supervised learning has unwavering to be superior to unsupervised mode of view verdict. The proposed paper has given a comparative study of naïve Bayes and SVM on the opinions of the reviewers of the stock market. No system has been created for sentiment analysis in the share market. Thus, new field is chosen and worked upon and its result can helps the user to take better decisions in the field of stock market.