SAFE

This code implements SAFE: Similarity-Aware Multi-modal Fake News Detection model.

Resource

Dataset

We use FakeNewsNet dataset and provide our data in this link. For the latest verision of FakeNewsNet, please directly check out: https://github.com/KaiDMML/FakeNewsNet.

Image captioning tool

We use Show and Tell to abstract the content of images.

Word2vec embedding

We embed words use pre-trained word vectors glove.840B.300d and the embedding tool SIF. The computation of glove.840B.300d word map is time-consuming, in order to provide more convenience we upload (words, We), which is the result of data_io.getWordmap(wordfile) in SIF. Please check embedding branch for the modified code and embedding results.

Requirements

• Python 3.7
• TensorFlow 2.2
• xlwt
• nltk

Getting Started

Install requirements

pip install -r requirements.txt

Train

python3 helper.py
python3 train.py

Test

python3 test.py

Citation

If you use this code for your research, please cite our paper:

@inproceedings{zhou2020multimodal,
  title={SAFE: Similarity-Aware Multi-modal Fake News Detection},
  author={Zhou, Xinyi and Wu, Jindi and Zafarani, Reza},
  booktitle={Pacific-Asia Conference on Knowledge Discovery and Data Mining},
  pages={354--367},
  year={2020},
  organization={Springer}
}

Contact

If you have any question, please contact zhouxinyi@data.syr.edu.