Machine Learning Tweets analysis Sentiment Analysis Stock Prediction Python

Stock Market Prediction using Sentiment Analysis of Tweets

by Achyutha Bharadwaj

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Info

  • Implemented web crawlers to extract Tweet data and Stock Market Price.
  • NLP techniques like Tokenization, Stop-word-removal, Stemming are used to perform language modeling and Sentiment Analysis on Twitter data.
  • Machine learning techniques like Support Vector Machines, Logistic Regression and Multi-layer Perceptron are used on the classified sentiment data along with stock market price to predict the trends of stock market price.
  • The ML models predicted the prices most accurately when Topic Modeling was used. Considering past 5 days of tweet sentiments, we were able to predict change in stock prices with close to 70% accuracy.