AAGCN-ACSA

EMNLP 2021

Introduction

This repository was used in our paper:

Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge
Bin Liang^*, Hang Su^*, Rongdi Yin, Lin Gui, Min Yang, Qin Zhao, Xiaoqi Yu, and Ruifeng Xu. Proceedings of EMNLP 2021

Please cite our paper and kindly give a star for this repository if you use this code.

Requirements

• Python 3.6
• PyTorch 1.0.0
• SpaCy 2.0.18
• numpy 1.15.4

Usage

• Install SpaCy package and language models with

pip install spacy

and

python -m spacy download en

• Generate aspect-focused graph with

python generate_graph_for_aspect.py

• Generate inter-aspect graph with

python generate_position_con_graph.py

Training

• Train with command, optional arguments could be found in train.py & train_bert.py

• Run intergcn: ./run_intergcn.sh

• Run afgcn: ./run_afgcn.sh

• Run intergcn_bert: ./run_intergcn_bert.sh

• Run afgcn_bert: ./run_afgcn_bert.sh

Citation

The BibTex of the citation is as follow: