Public health institutions, such as the World Health Organization (WHO), include some social networking tools (such as Facebook, Twitter and others) as a crucial part in the dissemination of reliable health information, monitoring a health crisis and containing of online rumors. In Brazil, the Ministry of Health, to combat the spread of fake news, launched a program, in which they made a WhatsApp number available to receive viral information and verify their veracity. However, the complexity of dealing with communication during a health crisis is quite high, as social media, compared to traditional media, are more difficult to monitor, track and analyse. At the moment, Brazil has been identified as one of main epicentres of the COVID-19 spreading, and to get the situation even worse, the current Brazilian President Jair Bolsonaro (as well as his right-wing supporters) is also responsible for spreading misinformation about the coronavirus in his social networks. Given this context, it is important to develop mechanisms to monitor and mitigate the dissemination of online fake news in Portuguese. The dataset presented in this paper is composed of 1299 rumors and non-rumors in Brazilian Portuguese identified by journalists and by the Brazilian Ministry of Health. It can be used to analyse the fake news composition and also to train computational models to detect COVID-19 fake news in Portuguese automatically.
Web Scrapping to https://www.boatos.org/tag/coronavirus, https://www.saude.gov.br/component/tags/tag/novo-coronavirus-fake-news, https://oglobo.globo.com/fato-ou-fake/