twitter-stock-sentiment : Stock market sentiment analysis using twitter

Sentiment Analysis of Tweets to find Relationship with the Stock Price Movement The project classifies the tweets related to stock market into three market sentiments viz, Bullish, Bearish and Neutral using various machine learning techniques like Naive Bayes, Maximum Entropy and SVM and finding their effectiveness on providing sentiment. Also a correlation can be found between sentiment of tweets and stock price movements.

Getting Started

Prerequisites

• Python 3.3, 3.4, 3.5 & 3.6 are supported.
• MongoDB

Dependencies

• Tweepy
• pymongo
• scikit-learn
• numpy
• scipy

Data Distribution for NLTK
Install using NLTK downloader: nltk.download()
For instructions please see http://www.nltk.org/
Download Stopwords and Punkt Word Tokenizer

Installing

git clone https://github.com/poojathakoor/twitter-stock-sentiment.git
cd twitter-stock-sentiment
pip install -r requirements.txt
cd twitter-stock-sentiment
python gui.py

Authors

Pooja Thakoor

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

• https://twitter.com/
• http://www.nltk.org/
• http://www.tweepy.org/
• https://www.mongodb.com