Semantic analysis score as input to LSTM model for improving stock price prediction accuracy I have created a univariate LSTM model that is predicting value of Open Price based on last 5 years opening price of a particular stock. I'm getting a decent accuracy. Now, I want to do sentiment analysis of the news data of the last 5 years of that stock and combine that score with my existing LSTM model in order to improve the predicted values of LSTM model. Does anyone has an idea whether this implementation is possible and if yes how can I proceed. Thanks in advance :)
It is possible. Your problem will then become multivariate, where on top of the opening price for a particular day, you would also add a sentiment score for that day.
LSTM can handle multiple inputs natively, so there shouldn't be much for you to change.