PyTorch implementation of "Exploring Graph-aware Multi-View Fusion for Rumor Detection on Social Media"
The two datasets we used are public datasets. You can obtain the data from corresponding official links.
Semeval 2017 The dataset supports stance classification (task A) and rumor detection (task B). In this paper, we focus on the task of rumor detection, and the stance labels are only used to visualize user stance in a post.
- python==3.8.8
- torch==1.8.1
- torch_geometric==2.0.1
- torch_cluster==1.5.9
- torch_spline_conv==1.2.1
- torch_scatter==2.0.8
- torch_sparse==0.6.12
- matplotlib==3.5.1
- packaging==21.3
- tabulate==0.8.9
If you are insterested in this work, and want to use the codes or results in this repository, please star this repository and cite by:
@article{wuexploring,
title={Exploring Graph-aware Multi-View Fusion for Rumor Detection on Social Media},
author={Wu, Yang and Yang, Jing and Zhou, Xiaojun and Wang, Liming and Xu, Zhen}
}