College admission deadlines are rapidly approaching for senior high school students. Being able to predict your chances of acceptance for your local or dream college based on simple information gives you an instant insight on what factors are influencing your results and by how much.

What it does

ChanceMe AI takes in all key indicators of your academic performance as well as the colleges you are interested in applying to, and produces a realistic result of your likelihood of acceptance. More precisely, it takes in numerical scores and analyzes the r/chanceme subreddit to judge the appeal of your extracurricular activities. It processes this data, and returns a final percentage score of your likelihood of acceptance. Judging extracurricular activities is possible through a natural language processing model that extrapolates a numerical sentiment value for a particular phrase.

How we built it

On top of the usual web development languages like HTML, CSS, and Javascript for the front-end, we used Python and a variety of its data analysis and networking libraries to do the Reddit web scraping and data processing on the back-end. The processing was all based around a reddit sentiment analysis library by KevHg.

Challenges we ran into

Timing was a large challenge, as well as 4-person virtual collaboration.

Accomplishments that we're proud of

With a local virtual back-end, our project does indeed produce realistic results. This was also our first time-based group hacking project, and we think it came out pretty well.

What we learned

We learned a great deal about web scraping, data organization, and synonymous front-end and back-end development with differnt languages on each end.

What's next for ChanceMe AI

Finalize the algorithm and host all of the processes remotely, so web deployment is possible.

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