Sentiment-aware stock market prediction: A deep learning method

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Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, background): “Similarly, the authors of [119] used sentiment classification (neutral, positive, negative) for the stock open or close price prediction with various LSTM models.”
Deep Learning for Financial Applications : A Survey (2020, methodology): “[157] Stocks of CSI300 index, OCHLV of CSI300 index 2009-2014 Sentiment Posts, Price data Naive Bayes + LSTM Precision, Recall, F1-score, Accu-”
Evaluation of bidirectional LSTM for short-and long-term stock market prediction (2018, methodology): “[19] attempted to improve the prediction model built using Long Short-Term Memory (LSTM) neural network by integrating a naı̈ve Bayes modeling technique to include and extract investor sentiment and market factors from forum posts.”
A Survey of Forex and Stock Price Prediction Using Deep Learning (2021, methodology): “[83] 90%-100% [25] It could be found that paper [25] performed best, which used LSTM model, and the paper's accuracy was in the range of 90%-100%.”
Applications of deep learning in stock market prediction: recent progress (2020, methodology): “…process of rescaling the input feature by the minimum and range, to make all the values lie between 0 and 1 (Wang & Wang, 2015; Gunduz et al., 2017; Li et al., 2017b; Singh & Srivastava, 2017; Althelaya et al., 2018; Althelaya et al., 2018; Baek & Kim, 2018; Chen et al., 2018a; Chung & Shin, 2018;…”