🎭 Sentiment Analysis of Twitter data using combined CNN and LSTM Neural Network models
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README.md

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Sentiment Analysis of Twitter data using a combined CNN-LSTM Neural Network model

Motivation

This project seeks to extend the work we did previously on sentiment analysis using simple Feed-Foward Neural Networks (Found here: paper & repo). Instead, we wish to experiment with building a combined CNN-LSTM Neural Net model using Tensorflow to perform sentiment analysis on Twitter data.

Dependencies

sudo -H pip install -r requirements.txt

Run the Code

  • On train.py change the variable MODEL_TO_RUN = {0 or 1}
    • 0 = CNN-LSTM
    • 1 = LSTM-CNN
  • Feel free to change other variables (batch_size, filter_size, etc...)
  • Run python train.py (or, with proper permissions, ./train.py

Code Structure

  • lstm_cnn.py : Contains the LSTM_CNN Model class to be instantiated.
  • cnn_lstm.py : Contains the CNN_LSTM Model class to be instantiated.
  • train.py : Main runner for the code. It instantiates a model, trains it and validates it.
  • batchgen.py : Contains a couple of functions needed to pre-process and tokenize the dataset.