Code and Data for "Characterizing Multi-Domain False News and Underlying User Effects on Chinese Weibo" (IP&M, 2022)

Preprint: https://arxiv.org/pdf/2205.03068

Article: https://www.sciencedirect.com/science/article/abs/pii/S0306457322000784

Chinese Brief: https://mp.weixin.qq.com/s/bZDTdwBzGrBKwPeImp1v-A

• Code: Code for Analysis of False News on Weibo Data Set.ipynb in this repo.
• Figures: The figures (in .pdf format) generated by running the Python code.
• Data: A Google Drive file that will be available after your application is approved (311MB) (Please import into your local MongoDB server)

Please fill in the Office Form: https://forms.office.com/r/9jNpP003Cp

• Python==3.7.3
• MongoDB==4.2.8

• pymongo==3.7.0
• pandas==0.23.4
• numpy==1.15.1
• scipy=1.1.0
• seaborn==0.9.0
• matplotlib==3.1.0

If you feel this GitHub repo is useful, please cite the following article:

@article{Multi-domain-false-news,
    title = {Characterizing Multi-Domain False News and Underlying User Effects on Chinese Weibo},
    author = {Sheng, Qiang  and Cao, Juan and Bernard, H. Russell and Shu, Kai and Li, Jintao, and Liu, Huan},
    journal = {Information Processing \& Management},
    doi = {10.1016/j.ipm.2022.102959},
    volume = {59},
    number = {4},
    pages = {102959},
    year = {2022},
    issn = {0306-4573}
}