Research Article
Research on Stock Forum Commentary Data Mining and Stock Prediction Based on the LSTM-RF Algorithm
@INPROCEEDINGS{10.4108/eai.2-12-2022.2328763, author={Gang Lei and Jinliang Wang and Chiyu Shi and Junyu Su}, title={Research on Stock Forum Commentary Data Mining and Stock Prediction Based on the LSTM-RF Algorithm }, proceedings={Proceedings of the 3rd International Conference on Big Data Economy and Information Management, BDEIM 2022, December 2-3, 2022, Zhengzhou, China}, publisher={EAI}, proceedings_a={BDEIM}, year={2023}, month={6}, keywords={lstm-rf algorithm; sentiment analysis; stock price prediction}, doi={10.4108/eai.2-12-2022.2328763} }- Gang Lei
Jinliang Wang
Chiyu Shi
Junyu Su
Year: 2023
Research on Stock Forum Commentary Data Mining and Stock Prediction Based on the LSTM-RF Algorithm
BDEIM
EAI
DOI: 10.4108/eai.2-12-2022.2328763
Abstract
As one of the important platforms for investors to exchange their views on stocks, the emotional tendency of stock commentary information influences investors' decisions to a certain extent. The monolithic model is ineffective in analyzing stock investors' sentiment and predicting stock prices. Therefore, we take the Sina stock forum as the entry point and use a web crawler to crawl the comments made by investors of the top 20 stocks in the Shanghai Stock Exchange and use RF to extract and classify the sentiment feature words to build an LSTM-RF stock price prediction model to predict stock price trends. The model can accurately predict the stock price trend.
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