pmsosa / Cs291k
🎭 Sentiment Analysis of Twitter data using combined CNN and LSTM Neural Network models
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CS291K
Sentiment Analysis of Twitter data using a combined CNN-LSTM Neural Network model
- Paper: https://www.academia.edu/35947062/Twitter_Sentiment_Analysis_using_combined_LSTM-CNN_Models
- Blog Post: http://konukoii.com/blog/2018/02/19/twitter-sentiment-analysis-using-combined-lstm-cnn-models/
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.
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