Author: Forte Martins, A. D.; Cabral, L.; Chaves Mourão, P. J.; Monteiro, J. M.; Machado, J.
Title: Detection of Misinformation About COVID-19 in Brazilian Portuguese WhatsApp Messages Cord-id: keeqpxdd Document date: 2021_1_1
ID: keeqpxdd
Snippet: During the coronavirus pandemic, the problem of misinformation arose once again, quite intensely, through social networks. In many developing countries such as Brazil, one of the primary sources of misinformation is the messaging application WhatsApp. However, due to WhatsApp’s private messaging nature, there still few methods of misinformation detection developed specifically for this platform. Additionally, a MID model built to Twitter or Facebook may have a poor performance when used to cla
Document: During the coronavirus pandemic, the problem of misinformation arose once again, quite intensely, through social networks. In many developing countries such as Brazil, one of the primary sources of misinformation is the messaging application WhatsApp. However, due to WhatsApp’s private messaging nature, there still few methods of misinformation detection developed specifically for this platform. Additionally, a MID model built to Twitter or Facebook may have a poor performance when used to classify WhatsApp messages. In this context, the automatic misinformation detection (MID) about COVID-19 in Brazilian Portuguese WhatsApp messages becomes a crucial challenge. In this work, we present the COVID-19.BR, a data set of WhatsApp messages about coronavirus in Brazilian Portuguese, collected from Brazilian public groups and manually labeled. Besides, we evaluated a series of misinformation classifiers combining different techniques. Our best result achieved an F1 score of 0.778, and the analysis of errors indicates that they occur mainly due to the predominance of short texts. When texts with less than 50 words are filtered, the F1 score rises to 0.857. © 2021, Springer Nature Switzerland AG.
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