/DUCK-code

Code for DUCK: Rumour Detection on Social Media by Modelling User and Comment Propagation Networks NAACL2022(https://aclanthology.org/2022.naacl-main.364/)

Primary LanguagePython

requirement packages

Dependencies:

python==3.7
torch==1.9.0+cu102
torchvision==0.10.0+cu102
torch-scatter==2.0.8
torch-sparse==0.6.11
torch-geometric==1.7.2
transformers==4.2.1
sckikit-learn==0.21.3
tqdm==4.62.0
numpy==1.19.5
pandas
matplotlib==2.2.3
networkx==2.2
scipy==1.2.0
pyro-ppl==0.3.0
networkx
pickle

required packages are in requirements.txt

pip install -r requirements.txt

running environment

data

All datasets are public accessible

Twitter15
[Twitter16] (https://www.dropbox.com/s/7ewzdrbelpmrnxu/rumdetect2017.zip?dl=0 )
[CoAID] (https://github.com/cuilimeng/CoAID) version 0.4
[WEIBO] (https://alt.qcri.org/~wgao/data/rumdect.zip)

data crawling tool

[twarc] (https://github.com/DocNow/twarc)

training the DUCK model

python3 train.py --datasetName 'Twitter15' --baseDirectory './data' --mode 'DUCK' --modelName 'DUCK'

comment graph data

python3 train.py --datasetName 'Twitter15' --baseDirectory './data' --mode 'CommentTree' --modelName 'Simple_GAT_BERT'

user graph data

python3 train.py --datasetName 'Twitter15' --baseDirectory './data' --mode 'UserTree' --modelName 'Simple_GAT_BERT'

run script

$ sh run.sh

publicaton

This is the source code for DUCK: Rumour Detection on Social Media by Modelling User and Comment Propagation Networks

If you find this code useful, please let us know and cite our paper.
If you have any question, please contact Lin at: s3795533 at student dot rmit dot edu dot au.