An Improved Machine Learning Algorithm for Stock Price Prediction

Twitter is being utilized to report and remark on market news. Currently, companies forecast stock prices using Twitter data. The paper discusses the merits and cons of Twitter. This paper investigates the effects of data quality, machine learning algorithm complexity, and the need for a realistic evaluation method on Twitter stock price forecasts. Proposed a hybrid algorithm for Twitter data forecasting. The proposed algorithm approach utilizes LSTM for feature extraction and RF for prediction. This Twitter investigation evaluated algorithms for predicting stock prices. A recent paper examined elements of stock price forecasting. This paper discusses the difficulties of predicting stock prices using tweets from Twitter, as well as ideas for improving the accuracy and robustness of machine learning models. The paper also uncovered limitations associated with using Twitter data to forecast stock prices.