# DualGCN-ABSA

**Repository Path**: zhou8827/DualGCN-ABSA

## Basic Information

- **Project Name**: DualGCN-ABSA
- **Description**: Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-12-06
- **Last Updated**: 2021-12-06

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# DualGCN

Code and datasets of our paper "[Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis](https://aclanthology.org/2021.acl-long.494/)" accepted by ACL 2021.



## Requirements

- torch==1.4.0
- scikit-learn==0.23.2
- transformers==3.2.0
- cython==0.29.13
- nltk==3.5

To install requirements, run `pip install -r requirements.txt`.

## Preparation

1. Download and unzip GloVe vectors(`glove.840B.300d.zip`) from [https://nlp.stanford.edu/projects/glove/](https://nlp.stanford.edu/projects/glove/) and put it into  `DualGCN/glove` directory.

2. Prepare vocabulary with:

   `sh DualGCN/build_vocab.sh`

3. Download the best model [best_parser.pt](LAL-Parser/best_model/readme.md) of [LAL-Parser](https://github.com/KhalilMrini/LAL-Parser).

## Training

To train the DualGCN model, run:

`sh DualGCN/run.sh`

## Credits

The code and datasets in this repository are based on [ABSA-PyTorch](https://github.com/songyouwei/ABSA-PyTorch) and [CDT_ABSA](https://github.com/Guangzidetiaoyue/CDT_ABSA).



## Citation

If you find this work useful, please cite as following.

```
@inproceedings{li-etal-2021-dual-graph,
    title = "Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis",
    author = "Li, Ruifan  and
      Chen, Hao  and
      Feng, Fangxiang  and
      Ma, Zhanyu  and
      Wang, Xiaojie  and
      Hovy, Eduard",
    booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.acl-long.494",
}
```