• A new stock market forecasting model utilizing sentiment analysis and attention mechanism is presented in this paper to forecast AAPL during the COVID-19 pandemic
• Scraped tweets from the Stock investing community Stocktwits and developed a Bidirectional LSTM with GloVe word embeddings to predict whether the tweet is bullish or bearish
• Developed an LSTM with an attention mechanism and sentiments from the text classifier to forecast stock market prices across 2020
• Stock market sentiment analyzer reached accuracy of 74% (5% higher than previous papers) and LSTM model with sentiment analysis and attention mechanism increased R-squared by over 10% from the baseline LSTM
• Accepted into 2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference on the Big Data track