Inspiration

We were inspired to work on this project due to the biases present throughout coverage of breaking news stories across the world, and a lack of knowledge of background context or historical precedence of what led to them occurring.

What it does

It takes a news article and scans the text for indices that could determine potential bias. When this is done, an AI analyses is displayed with a Overton window indicator of where the article stands as well as the key words that are responsible for that framing. There is also a timeline of key contextual events that are related to the headline and help explain how we got to it.

How we built it

We used HTML/CSS, Javascript, and applied the OpenAI API.

Challenges we ran into

Figuring out how to get testing done with low amounts of credits. Were not able to work on getting a plug-in version.

Accomplishments that we're proud of

Developing a tool to help people learn more about the stories they read.

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