NOTE: We were not able to publish a youtube video in time. If we are able to edit in the future, we will provide a link, but for the time being get Rick Rolled.
UPDATE: WE HAVE A LINK!
Inspiration
We wanted to observe the overall outlook in regard to COVID-19.
What it does
Our project determines whether tweets about COVID-19 share positive or negative sentiment.
How we built it
Data is live-streamed from twitter to a Google Cloud Database. The data is run through a machine learning model which predicts if the tweet has either positive or negative sentiment. These results are displayed on a Streamlit dashboard.
Challenges we ran into
It took us a long time to figure out how to chain all the data. Additionally, we had a hard time connecting the Google Cloud Database using Python.
Accomplishments that we're proud of
Overcoming our previously mentioned challenges had to have been the most fulfilling moment of the HackGT 7.
What we learned
We learned better and more efficient ways to scrape for data, create machine learning models, and connect to Google Cloud Databases using Python.
What's next for COVID-19 Sentiment Analysis Dashboard
The next step for COVID-19 Sentiment Analysis Dashboard would be to improve the modeling.
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