Sentiment Analysis using LSTM model with Scikit-learn and Keras

The notebook is also available at as a kaggle kernal try it out there with free gpu and hastle free python environment.

Dataset

First GOP Debate Twitter Sentiment About this Dataset This data originally came from Crowdflower's Data for Everyone library.

As the original source says, We looked through tens of thousands of tweets about the early August GOP debate in Ohio and asked contributors to do both sentiment analysis and data categorization. Contributors were asked if the tweet was relevant, which candidate was mentioned, what subject was mentioned, and then what the sentiment was for a given tweet. We've removed the non-relevant messages from the uploaded dataset.

Details about model

• model contains 3 layers (Embedding, LSTM, Dense with softmax).
• Upsampling is used to balance the data of minority class.
• Loss fuction with different class weight in keras to further reduce class imbalance.

To Do

• Add requirement.txt
• Add bash script to install required packages