A successful business knows what its customers need and feel about their products. Therefore we developed a tool for generating Emotion Analysis about a business.

What it does

Using Long Short Term Memory (LSTM) we are training a model to classify emotional state of a person writing that review. Using those classifications we are providing analysis report about emotion distribution of that business

How we built it

We used tensorflow library to train LSTM to classify emotional state. We used SemEval 2007 Task 14 for training data. Using Flask we created web application's architecture User review about a business were collected by scraping Yelp website. Reviews were classified using trained LSTM model and report was generated using Matplotlib.

Challenges we ran into

Preprocessing the training data to make the data usable for training purpose Modifying LSTM model parameters for improving accuracy

Accomplishments that we're proud of

Learned Tensorflow and implemented LSTM

What we learned

Tensorflow LSTM RNN

What's next for Emotion Analysis for Yelp reviews

Deploying for different business in different domain. For example: For Amazon Products

Built With

Share this project: