Challenge 1: Enable companies and organizations to have the ability to understand customer/user sentiments and thoughts quickly

What it does

sentimentalReviews is a website, in which users can leave reviews for a business.

Also accompanying is a mobile app with similar functions.

The reviews are then stored in a sqLite database, in which they are classified as "positive", "negative", and "neutral" according to a classifier provided by NLTK.

The data is then visualized using matPlotLib.

How we built it

We used python with the Django framework for the backend. We used html/css/bootstrap for the frontend. We used matPlotLib and NLTK to analyze and visualize the user reviews.

Challenges we ran into

-accessing the database in dJango models was actually pretty hard: took a lot of googling to figure out -learning about form processing in Django was really difficult

Accomplishments that we're proud of

Built a fully functioning website: with both a frontend and a backend. First time accomplished by all members.

What we learned

What's next for sentimentalReviews

Right now, we're using a pre-trained classifier that was trained using Twitter data. Ideally, if there was enough time, we could manually classify restaurant reviews, and train our own neural net for more accurate classification.

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