# FakeCovid -- A Multilingual Cross-domain Fact Check News Dataset for COVID-19

arXiv: https://arxiv.org/abs/2006.11343 · HTML: https://mlsanity.com/paper/2006.11343/

## Key facts

- Cited by 61 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2020.

## Built on by (most cited first, 30 of 61)

- [A Survey on Automated Fact-Checking](https://mlsanity.com/paper/2108.11896/) (2021)
- [End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models](https://mlsanity.com/paper/2205.12487/) (2022)
- [X-FACT: A New Benchmark Dataset for Multilingual Fact Checking](https://mlsanity.com/paper/2106.09248/) (2021)
- [Scientific Fact-Checking: A Survey of Resources and Approaches](https://mlsanity.com/paper/2305.16859/) (2023)
- [Multimodal Automated Fact-Checking: A Survey](https://mlsanity.com/paper/2305.13507/) (2023)
- [Overview of the HASOC track at FIRE 2020: Hate Speech and Offensive Content Identification in Indo-European Languages](https://mlsanity.com/paper/2108.05927/) (2021)
- [CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking](https://mlsanity.com/paper/2206.11863/) (2022)
- [EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification](https://mlsanity.com/paper/2310.09754/) (2023)
- [CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweets](https://mlsanity.com/paper/2204.12164/) (2022)
- [Check-COVID: Fact-Checking COVID-19 News Claims with Scientific Evidence](https://mlsanity.com/paper/2305.18265/) (2023)
- [Overview of the CLEF--2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News](https://mlsanity.com/paper/2109.12987/) (2021)
- [COVID-19 Named Entity Recognition for Vietnamese](https://mlsanity.com/paper/2104.03879/) (2021)
- [Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checking](https://mlsanity.com/paper/2411.05375/) (2024)
- [Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages](https://mlsanity.com/paper/2112.09301/) (2021)
- [Transformer-based Language Model Fine-tuning Methods for COVID-19 Fake News Detection](https://mlsanity.com/paper/2101.05509/) (2021)
- [Do We Need Language-Specific Fact-Checking Models? The Case of Chinese](https://mlsanity.com/paper/2401.15498/) (2024)
- [Transformer based Automatic COVID-19 Fake News Detection System](https://mlsanity.com/paper/2101.00180/) (2021)
- [Real-time Factuality Assessment from Adversarial Feedback](https://mlsanity.com/paper/2410.14651/) (2024)
- [Dataset of Fake News Detection and Fact Verification: A Survey](https://mlsanity.com/paper/2111.03299/) (2021)
- [Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims](https://mlsanity.com/paper/2204.12294/) (2022)
- [EUvsDisinfo: A Dataset for Multilingual Detection of Pro-Kremlin Disinformation in News Articles](https://mlsanity.com/paper/2406.12614/) (2024)
- [A Guide to Misinformation Detection Data and Evaluation](https://mlsanity.com/paper/2411.05060/) (2024)
- [Beyond Translation: LLM-Based Data Generation for Multilingual Fact-Checking](https://mlsanity.com/paper/2502.15419/) (2025)
- [Cross-lingual COVID-19 Fake News Detection](https://mlsanity.com/paper/2110.06495/) (2021)
- [CsFEVER and CTKFacts: Acquiring Czech data for fact verification](https://mlsanity.com/paper/2201.11115/) (2022)
- [Using Persuasive Writing Strategies to Explain and Detect Health Misinformation](https://mlsanity.com/paper/2211.05985/) (2022)
- [JailNewsBench: Multi-Lingual and Regional Benchmark for Fake News Generation under Jailbreak Attacks](https://mlsanity.com/paper/2603.01291/) (2026)
- [A transformer based approach for fighting COVID-19 fake news](https://mlsanity.com/paper/2101.12027/) (2021)
- [Mitigation of Diachronic Bias in Fake News Detection Dataset](https://mlsanity.com/paper/2108.12601/) (2021)
- [Challenges and Considerations with Code-Mixed NLP for Multilingual Societies](https://mlsanity.com/paper/2106.07823/) (2021)

## Abstract (arXiv)

In this paper, we present a first multilingual cross-domain dataset of 5182 fact-checked news articles for COVID-19, collected from 04/01/2020 to 15/05/2020. We have collected the fact-checked articles from 92 different fact-checking websites after obtaining references from Poynter and Snopes. We have manually annotated articles into 11 different categories of the fact-checked news according to their content. The dataset is in 40 languages from 105 countries. We have built a classifier to detect fake news and present results for the automatic fake news detection and its class. Our model achieves an F1 score of 0.76 to detect the false class and other fact check articles. The FakeCovid dataset is available at Github.