├── Data
│ ├── en_dup.csv
│ └── news
│ └── twitter
├── Data Analysis
│ └── PowerLaw Analysis.pdf
├── Data Collecting
│ └── snopes.py
├── LICENSE
└── README.md
snopes.py
by Tianqi- It is used to collect data from website www.snopes.com and qc.wa.news.cn (departed)
- PowerLaw Analysis includes the statistical analysis of rumor popularity data.
- Pre-processed data for deep learning tasks: https://drive.google.com/drive/folders/1jpnyHw1_XWR7lZTSb86AYWFsNC0bNEwO?usp=sharing.
- Veracity analysis https://colab.research.google.com/drive/1qtt0X9a7I9vBZPoZ-PzyhDuF5L_G3thj?usp=sharing
- Sentiment analysis https://colab.research.google.com/drive/1CyGtXPSol_Ayt_WR7zsq60M2Q5kDUofd?usp=sharing
- Stance analysis https://colab.research.google.com/drive/1ItGmEvumyOesXeB2dV7w5cnjRW9fTAKL?usp=sharing
- VAE model source https://www.researchgate.net/profile/Paul-Bogdan/publication/341128443_VRoC_Variational_Autoencoder-aided_Multi-task_Rumor_Classifier_Based_on_Text/links/5f1467fe92851c1eff1e647e/VRoC-Variational-Autoencoder-aided-Multi-task-Rumor-Classifier-Based-on-Text.pdf
-
news
- news.csv (4129) and subfolder of each news
- The number of subfolder records: 3936
-
twitter
- Twitter.csv (2705) and subfolder of each twitter
- The number of subfolder records: 1383
-
en_dup.csv
- Unprocessed data with both news and twitter records.
- The number of records: 7179 (with duplication).
- Part of data are collected manually by keywords searching from sources such as twitter.com.
- Data from www.snopes.com and qc.wa.news.cn are collected by 'snopes.py'.
- We thank Tianqi, Wenshuo, Jianni, Xiaofeng, and Hanlong for rumor data collection and labeling.
Cheng, Mingxi, et al. "A COVID-19 Rumor Dataset." Frontiers in Psychology 12 (2021): 1566.
@article{cheng2021covid,
title={A COVID-19 Rumor Dataset},
author={Cheng, Mingxi and Wang, Songli and Yan, Xiaofeng and Yang, Tianqi and Wang, Wenshuo and Huang, Zehao and Xiao, Xiongye and Nazarian, Shahin and Bogdan, Paul},
journal={Frontiers in Psychology},
volume={12},
pages={1566},
year={2021},
publisher={Frontiers}.
}.
Link to paper: https://www.frontiersin.org/articles/10.3389/fpsyg.2021.644801/full