north0n-FI/Twitter-moods-as-stock-price-predictors-on-Nasdaq
An attempt to predict next day's stock price movements using sentiments in tweets with cashtags. Six different ML algorithms were deployed (LogReg, KNN, SVM etc.). Main libraries used: Pandas & Numpy
This project explores whether public mood and sentiment expressed in tweets can predict daily stock price movements on the Nasdaq. By analyzing tweets containing cashtags and their sentiment, it attempts to forecast if a stock will rise or fall the next day. This is for financial analysts, traders, or investors interested in using social media sentiment as an indicator for short-term stock market trends.
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Use this if you want to investigate the potential impact of Twitter sentiment on daily Nasdaq stock price changes and are comfortable working with data analysis workflows.
Not ideal if you are looking for a ready-to-deploy, high-frequency trading algorithm or a guaranteed profit-making tool.
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Jun 04, 2019
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