Sentiment Lexicon for stock market prediction
Not readily available, but trivial to build on your own. Simply download a sentiment annotated twitter dataset, construct a dictionary of words for it, iterate over the entries and add +1/(-1) to positive(/negative) words. Finally, divide each word's values by its respective occurrence count and you'll have a naive sentiment score for each word, with values close to 1(/-1) indicating strong sentiment charge, which you can use for your BoW task.
I am making a Stock Market Predictor machine learning application that will try to predict the price for a certain stock. It will take news articles/tweets regarding that particular company and the company's historical data for this reason.
My issue is that I need to first construct a sentiment analyser for the headlines/tweets for that company. I dont want to train a model to give me the sentiment scores rather, I want a sentiment lexicon that contains a bag of words related to stock market and finance.
Is there any such lexicons/dictionaries available that I can use in my project?
Thanks