Inspiration
We wanted to put the power of voting into the peoples' hands considering the election. We thought it would be interesting to see who Twitter users approved for in the election.
What it does
The program scrapes through twitter for trump-related tweets and uses sentiment analysis to find if a twitter user approves or disapproves of trump. We then calculate biden's approval using trump's approval and "Twitter's vote" updates every 4-5 hours.
How I built it
We built the project using natural language processing, twitter API, and React.
Challenges I ran into
Running the machine learning algorithm
Accomplishments that I'm proud of
Finally putting backend, frontend, and machine learning algorithm together.
What I learned
We learned about machine learning, natural language processing, Django, React, and more.
What's next for Twitter Votes
We're looking to work on this in the future to make the code more efficient.
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