Inspiration
Investing in the stock market can require research into the sentiment of traders in real time. When I do my research I need to have multiple screens to keep track of sentiments. This leads me to do my research with manual queries on twitter to follow sentiments.
What it does
This application automates this process and displays the sentiments of twitter users' in an straightforward manner.
How I built it
The application is created using React and Flask. It uses an LSTM model trained on the Sentiment140 and served as a REST API to the ReactJS frontend.
Challenges I ran into
I ran into issues training my model as it took too long to train.
Accomplishments that I'm proud of
The UI is elegant and easy to understand.
What I learned
Time management is important when creating projects. If I had began with training my model, I would have been able to create a functioning product.
What's next for Twitter Sentiment Analysis React App
I plan to make use of the thinkorswim api to include real time stock charts when performing queries on ticker symbols.
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