Investigating Typed Syntactic Dependencies for Targeted Sentiment Classification Using Graph Attention Neural Network

This repository contains the code for the paper "Investigating Typed Syntactic Dependencies for Targeted Sentiment Classification Using Graph Attention Neural Network", IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP)

Setup

This code runs Python 3.6 with the following libraries:

• Pytorch 1.2.0
• Transformers 2.9.1
• GTX 1080 Ti

You can also create an virtual environments with conda by run

conda env create -f requirements.yaml

Get start

1. Prepare data

   • Restaurants, Laptop, Tweets and MAMS dataset. (We provide the parsed data at directory dataset)

   • Downloading Glove embeddings (available at here), then run

     awk '{print $1}' glove.840B.300d.txt > glove_words.txt
     

     to get glove_words.txt.

2. Build vocabulary

   bash build_vocab.sh
   

3. Training Go to Corresponding directory and run scripts:

   bash run-MAMS-glove.sh
   bash run-MAMS-BERT.sh
   

4. The saved model and training logs will be stored at directory saved_models

Results

References

@ARTICLE{bai21syntax,  
	author={Xuefeng Bai and Pengbo Liu and Yue Zhang},  
	journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},   
	title={Investigating Typed Syntactic Dependencies for Targeted Sentiment Classification Using Graph Attention Neural Network},   
	year={2021},  
	volume={29}, 
	pages={503-514},  
	doi={10.1109/TASLP.2020.3042009}
}