As the presence of internet public figures increase, their influence over others increase. More and more "ideal" role models go behind the loyalty of their followers by purposely advertising companies for personal gain. Powered by 16 hours of brainstorming, VR games, 6 hours of sleep deprivation and leidos's machine learning challenge.

What it does

The app uses a comprehensive algorithm to detect whether or not a given twitter user is advertising sponsored content.

How we built it

With the power of 3 workers and one sleepy driver, an application to detect sell outs was created over a span of 24 hours. We utilized twitter's api to gather tweets from users and feed that through a machine learning algorithm to detect sponsored content.

Challenges we ran into

Twitters api was hard to read and to use. Brainstorming of how we were going to determine whether a user advertised sponsored content took a long time to figure out. Accidentally closing cloud shell while having too many tabs open on a computer.

Accomplishments that we're proud of

We are proud that we were able to implement machine learning into a hack to an everyday problem, sponsored content. We are also proud that we were able to create a finished hack with two first-time hackathon hackers.

What we learned

We learned that today, a lot of resources are available online and with enough dedication and time, a desired hack can be created.

What's next for Find out Sellout

find out right after we take a nap

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