Sentiment Analysis for Stock Prediction Using Mass Media Sources

“Sentiment Analysis for Stock Prediction Using Mass Media Sources” introduces a groundbreaking approach to forecasting stock movements by harnessing sentiment analysis applied to economic news gathered from a diverse range of mass media sources. The project encompasses the creation of a comprehensive system that systematically scrapes economic news websites to gather information relevant to specific companies. This data is then meticulously analyzed to discern the sentiments expressed in the news articles. Subsequently, cutting-edge Machine learning techniques are put to use to anticipate potential fluctuations in the stock prices of the target companies. This holistic approach capitalizes on the amalgamation of Natural language processing which combined with machine learning techniques, and real-time news data, delivering invaluable insights for both investors and traders.