sukeey / SSEGCN-ABSA

SSEGCN: Syntactic and Semantic Enhanced Graph Convolutional Network for Aspect-based Sentiment Analysis

SSEGCN-ABSA

Code and datasets of our paper "SSEGCN: Syntactic and Semantic Enhanced Graph Convolutional Network for Aspect-based Sentiment Analysis" accepted by NAACL 2022.

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/ and put it into SSEGCN/glove directory.

2. Prepare dataset with:

   python preprocess_data.py

3. Prepare vocabulary with:

   sh build_vocab.sh

Training

To train the SSEGCN model, run:

sh run.sh

Credits

The code and datasets in this repository are based on DualGCN_ABSA .