  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.
