SENTIMENT ANALYSIS OF STOCK NEWS USING NLTK



EOI: 10.11242/viva-tech.01.05.232

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Citation

Ms. Hardik Raut, Ms. Rohini Hodge, Ms. Harshal Bhoir, Prof.Ameya purandare , "SENTIMENT ANALYSIS OF STOCK NEWS USING NLTK ", VIVA-IJRI Volume 1, Issue 5, Article 232, pp. 1-6, 2022. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Efficient Market Hypothesis is the popular theory about stock prediction. With its failure much research has been carried in the area of prediction of stocks. This project is about taking non quantifiable data such as financial news articles about a company and predicting its future stock trend with news sentiment classification. Assuming that news articles have impact on stock market, this is an attempt to study relationship between news and stock trend. To show this, we created a NLTK models which depict polarity of news articles being positive or negative. Experiments are conducted to evaluate various aspects of the proposed model. The NLTK model is accurate and this tool is able to determine the emotional values without neutral sections. Comparing these results with the movement of stock market values in the same time periods, we can establish the moment of the change occurred in the stock values with sentiment analysis of economic news headlines. The accuracy of the prediction model is more than 80% and in comparison, with news random labelling with 50% of accuracy; the model has increased the accuracy by 30%.

Keywords

blockchain , Stocks, NTLK

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