Real-Time Stock Market Prediction Based On Social Sentiment Analysis Using Machine Learning

Authors

  • D. SATHISH KUMAR
  • P. KARTHIK RAGAVUG
  • A.Arun

Keywords:

Machine Learning, Stocks, Sentiment analysis, Web Scraping, client Interface

Abstract

Machine learning area unit being employed in conjunction with data processing to solve real world problems. These techniques have evidenced to be extremely effective, yielding most accuracy with nominal quantity of investment and conjointly saving huge amount of time. To increase the annual income, People started looking towards stock investments as a More feasible possibility. With expert guidance and intelligent designing, we are able to nearly double our annual revenue through stock returns stock investment still remains a risky proposition for several people. With the help of Sentiment analysis on the tweets collected from Twitter API and with the closing values of stocks, Wecreate a system which can forecast the stock price movement and we can build a web interface to access the Predicted Information. We seek to develop the system to use real-time data and use it to train the model and update the model using stock data apisor webs craping stock data and twitter apis.

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Published

2023-12-21

How to Cite

D. SATHISH KUMAR, P. KARTHIK RAGAVUG, & A.Arun. (2023). Real-Time Stock Market Prediction Based On Social Sentiment Analysis Using Machine Learning. Elementary Education Online, 19(3), 4329–4334. Retrieved from https://ilkogretim-online.org/index.php/pub/article/view/6490

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