What it does

Uses machine learning sentiment analysis algorithms to determine the positive or negative characteristics of a comment or tweet from social media. This was use in large numbers to generate a meaningful average score for the popularity of any arbitrary search query.

How we built it

Python was a core part of our framework, as it was used to intelligently scrap multiple social media sites and was used to calculate the sentiment score of comments that had keywords in them. Flask was also used to serve the data to a easily accessible and usable web application.

Challenges we ran into

The main challenge we faced was that many APIs were changed or had outdated documentation, requiring us to read through their source code and come up with more creative solutions. We also initially tried to learn react.js, even though none of us had ever done front-end web development before, which turned out to be a daunting task in such a short amount of time.

Accomplishments that we're proud of

We're very proud of the connections we made and creating an application on time!

What's next for GlobalPublicOpinion

We hope to integrate more social media platforms, and run a statistical analysis to prevent potential bias.

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