Yelp User Review NLP project

Yelp_Review_NLP_project

Text Analysis and Prediction with Neural Network

In this notebook, I built four text classification neural network models to predict yelp users’ ratings based on their text reviews.

Backgroud: With so many unstructured data online, in the form as text, video and sounds, how can we turn them into structured data?

Nowadays we have access to thousands of reviews/comments on different social medias, while some reviews come with numeric ratings (like those on app Yelp), some don’t (like those on Twitter). Business owners can certainly trace reviews/comments from customers’ posts on all sorts of popular social media platfloms, however the process could become tedious especially when the number of reviews is large and customers’ feedback keep changing overtime. For another, the conclusion from human interpretation is more often towards qualitative, thus it’s more difficult to compare to performances in the past. For those reviews/comments that don’t come with numeric ratings, if we are able to label these reviews as positive or negative (or on a scale of 1 to 5) by training models with labeled data(yelp data), we can help business owners to keep track of the feedback from customers in a faster and more interpretable way, so that they can adjust their services and offerings in response to customers’ most-recent feedback.

Problem Statement The purpose of the project is to gain an understanding of yelp users’ reviews and to predict yelp users’ sentimental feedback based on their text reviews.