Inspiration
If you ever talk to a small business owner, they always complain about the false negative reviews. We heard of this issue from 2 different small restaurant owners the night before the hackathon, so hearing the CBRE challenge gave us the inspiration. We decided to make an app to make it easier to know the true sentiment of a place, by chacking the valudity of the review as well as how positive/negative the language is, therefore using the language to find the review.
What it does
Looks at the trending popularity of a specific user or company over time. It uses surveys, reviews, and social media posts to do so.
How we built it
We used bootstrap for the css, react for the front end, and flask for the backend. We have used machine learning to create our model for the prediction of sentiments through word embeddings.
Challenges we ran into
Merging up everything was the main challenge and finding out different type of analysis to filter of useful comments.
Accomplishments that we're proud of
We are proud of our team effort in making this product.
What we learned
We learning to actually use machine learning models in the web application through rest api.
What's next for Review it
We can add more review filters and handle cases for super large comments.
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