Twitter Sentiment Analysis Challenge for Learn Python for Data Science #2 by @Sirajology on Youtube
##Overview
This is the code for the Twitter Sentiment Analyzer challenge for 'Learn Python for Data Science #2' by @Sirajology on YouTube. The code uses the tweepy library to access the Twitter API and the TextBlob library to perform Sentiment Analysis on each Tweet. We'll be able to see how positive or negative each tweet is about whatever topic we choose.
##Dependencies
- tweepy (http://www.tweepy.org/)
- textblob (https://textblob.readthedocs.io/en/dev/)
Install missing dependencies using pip
##Usage
Once you have your dependencies installed via pip, run the script in terminal via
python demo.py
##Challenge
Instead of printing out each tweet, save each Tweet to a CSV file with an associated label. The label should be either 'Positive' or 'Negative'. You can define the sentiment polarity threshold yourself, whatever you think constitutes a tweet being positive/negative. Push your code repository to github then post it in the comments. I'll give the winner a shoutout a week from now!
##Credits
This code is 100% Siraj baby.