The code is related to the paper below: Jiao Qiao, Xianghua Li, Chao Gao, Lianwei Wu, Junwei Feng, Zhen Wang, Improving multimodal fake news detection by leveraging cross-modal content correlation, Information Processing and Management, 2025, 62(5): 104120.
The two datasets used for this project are publicly accessible, and their links are provided below.
In this project, due to upload size limitations for some data, the files in /data/weibo/processed/crops/ used can be downloaded via Google Drive.
We train our model on Python 3.7.0 and Pytorch 1.8.0. And your environment should have some packages as follows:
clip==1.0
cn_clip==1.5.1
importlib_metadata==6.0.0
langdetect==1.0.9
matplotlib==2.2.4
numpy==1.21.6
opencv_python==4.7.0.68
pandas==1.1.5
Pillow==9.5.0
scikit_learn==1.0.2
seaborn==0.12.2
torchtext==0.15.2
tqdm==4.64.1
transformers==4.25.1
After installing the environment, in the code directory, modify the save paths in main.py, process_image_weibo.py, and process_text_weibo.py.
First, execute process_text_weibo.py to obtain the complete text preprocessing results.
Next, run process_image_weibo.py to obtain the image preprocessing results.
Run main.py to perform the training process.
