CHECKED: Chinese COVID-19 Fake News Dataset
CHECKED, a Chinese COVID-19 fake news dataset from the microblog platform Weibo (Yang, Zhou and Zafarani, Social Network Analysis and Mining 2021): 2,104 microblogs posted between 2019-12-31 and 2020-08-30, 344 labelled fake (each with the expert analysis that identified it as false) and 1,760 real, with the 1,185,701 comments and 1,868,174 reposts (forwards) they received, including their text, date and hashed author. Microblog IDs and user IDs are replaced by 32-character hashes and user names are not released.
Cite this dataset at
checked-chinese-covid-news.echo.directory
Analytics
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Computed over the full corpus.
Record
- Catalog key
checked- Authors
- Yang, Chen; Zhou, Xinyi; Zafarani, Reza
- Year
- 2021
- DOI / arXiv
- 10.1007/s13278-021-00766-8
- License
- Academic use only (see GitHub) (LicenseRef-Research-Only)
- Records
- 2,104
- Languages
- zh
- Collected
- 2020-2021 (2020s)
- Tasks
- Fake news detection inferred
- Region
- China · East Asia (inferred: the platform is used mostly there)
Provenance
- Originally published at
- https://github.com/cyang03/CHECKED link checked
- Original files as received
- The source files, unconverted, kept for reference: mirrored on echo.directory on 2026-11-03, 762.4 MB across 2113 files. Checksums in MANIFEST.json. For use, start with the data package below.
- Data package
- Version 1.0.0 of this dataset as an ECHO Data Package: posts (3,055,979 rows), annotations (2,104 rows).
- Structure
- Labelled data, Text
Citations
CHECKED: Chinese COVID-19 fake news dataset
Chen Yang, Xinyi Zhou, R. Zafarani
Journal Article · Social Network Analysis and Mining · 2020
Cited by
- Deep learning for fake news detection: A comprehensive survey
Linmei Hu, Siqi Wei et al. · AI Open · 2022 · cited 175× - ANTi-Vax: a novel Twitter dataset for COVID-19 vaccine misinformation detection
Kadhim Hayawi, Sakib Shahriar et al. · Public Health · 2021 · cited 157× - Infodemic and fake news – A comprehensive overview of its global magnitude during the COVID-19 pandemic in 2021: A scoping review
V. Balakrishnan, W. Ng et al. · International Journal of Disaster Risk Reduction · 2022 · cited 119× - g2tmn at Constraint@AAAI2021: Exploiting CT-BERT and Ensembling Learning for COVID-19 Fake News Detection
Anna Glazkova, Maksim Glazkov et al. · CONSTRAINT@AAAI · 2020 · cited 71× - DC-CNN: Dual-channel Convolutional Neural Networks with attention-pooling for fake news detection
Kun Ma, Changhao Tang et al. · Applied intelligence (Boston) · 2022 · cited 55×
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- Cross-lingual COVID-19 Fake News Detection
Jiang-Shu Du, Yingtong Dou et al. · 2021 International Conference on Data Mining Workshops (ICDMW) · 2021 · cited 49× - Dataset of Fake News Detection and Fact Verification: A Survey
Taichi Murayama · arXiv.org · 2021 · cited 47× - MCFEND: A Multi-source Benchmark Dataset for Chinese Fake News Detection
Yu-Peng Li, Haorui He et al. · The Web Conference · 2024 · cited 42× - A systematic literature review and existing challenges toward fake news detection models
Minal Nirav Shah, A. Ganatra · Social Network Analysis and Mining · 2022 · cited 40× - COVID-19 fake news detection: A hybrid CNN-BiLSTM-AM model
Huo-Song Xia, Yuan Wang et al. · Technological forecasting & social change · 2023 · cited 39×
Citation data from Semantic Scholar, retrieved 2026-10-19.
How to cite
BibTeX
@misc{echo2026,
title = {ECHO: Exploratory Compendium of Humanity Online},
author = {Switzer, Braden and Zafarani, Reza},
year = {2026},
url = {https://echo.directory},
note = {Syracuse University}
}
@article{yang2021checked,
title = {{CHECKED}: Chinese {COVID-19} Fake News Dataset},
author = {Yang, Chen and Zhou, Xinyi and Zafarani, Reza},
journal = {Social Network Analysis and Mining},
year = {2021},
doi = {10.1007/s13278-021-00766-8}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Yang, C., Zhou, X., & Zafarani, R. (2021). CHECKED: Chinese COVID-19 Fake News Dataset [Data set]. https://doi.org/10.1007/s13278-021-00766-8
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Yang, Chen, et al. CHECKED: Chinese COVID-19 Fake News Dataset. 2021, doi.org/10.1007/s13278-021-00766-8.