MFCL

Source code for KBS accepted paper Multi-modal Robustness Fake News Detection with Mross-Modal and Propagation Network Contrastive Learning Contrastive Learning(MFCL)

Dataset

The datasets used in the experiments were based on the two publicly available Weibo and PHEME datasets released by Zheng et al. (2023) and Zubiaga et al. (2017). Preprocessed datasets are available at: Weibo https://www.dropbox.com/scl/fi/o7mhk0chqeo21pugequh2/Chinese.rar?dl=0&rlkey=zba9vldtuu3np7olct2dbzzb7 and PHEME https://www.dropbox.com/scl/fi/3oh12ur58a8d62l5vm5cb/PHEME.rar?dl=0&rlkey=jwq68ru9l10nbphcg5z8pnf1z

Dependencies

Our code runs with the following packages installed:

  python 3.9.0
  torch 1.13.1
  cuda 11.6.1
  pytorch-cluster  1.6.0             
  pytorch-scatter  2.1.0          
  pytorch-sparse  0.6.15
  torchvision  0.14.1	
  numpy  1.23.5
  yaml  0.2.5
  pandas  1.5.2
  scikit-learn 1.0.2

Run

Train and test

python ./Weibo/test.py -c ./Weibo/configs/weibo.yaml