Abstract
Stocks are a financial product with high risk but high reward and flexible trading that many investors prefer. If an investor can accurately predict the price of a stock, he or she will be rewarded handsomely. Stock prices, on the other hand, are influenced by a variety of factors, including macroeconomic conditions, market conditions, major socioeconomic events, investor preferences, and company business decisions. As a result, stock price forecasting has become the focus and difficulty of research in a variety of fields. Stock price prediction entails gathering news and commentaries, analyzing historical data, and determining the impact of news events on investor sentiment and stock price trends. The purpose of this paper is to provide an introduction to the application of text mining in the stock market, including commonly used text mining and prediction models, as well as to highlight problems in the field and suggest some future directions for improvement or research. Finally, many unresolved issues are raised in order to contribute to future research in this area.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Advances in Economics, Management and Political Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
