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2021 | OriginalPaper | Chapter

Detection of Misinformation About COVID-19 in Brazilian Portuguese WhatsApp Messages

Authors : Antônio Diogo Forte Martins, Lucas Cabral, Pedro Jorge Chaves Mourão, José Maria Monteiro, Javam Machado

Published in: Natural Language Processing and Information Systems

Publisher: Springer International Publishing

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Abstract

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.

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previous chapter Extracting Facts from Case Rulings Through Paragraph Segmentation of Judicial Decisions

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http://piaui.folha.uol.com.br/lupa/.

http://www.boatos.org/.

https://gitlab.com/jmmonteiro/misinformation_covid19.

Choudrie, J., Banerjee, S., Kotecha, K., Walambe, R., Karende, H., Ameta, J.: Machine learning techniques and older adults processing of online information and misinformation: a covid 19 study. Comput. Hum. Behav. 119, 106716 (2021). https://doi.org/10.1016/j.chb.2021.106716CrossRef

Elhadad, M.K., Li, K.F., Gebali, F.: Detecting misleading information on COVID-19. IEEE Access 8, 165201–165215 (2020). https://doi.org/10.1109/ACCESS.2020.3022867CrossRef

Garimella, K., Tyson, G.: WhatsApp, doc? A first look at WhatsApp public group data. arXiv preprint arXiv:1804.01473 (2018)

Giachanou, A., Zhang, G., Rosso, P.: Multimodal multi-image fake news detection. In: 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), pp. 647–654 (2020). https://doi.org/10.1109/DSAA49011.2020.00091

Kim, S.B., Han, K.S., Rim, H.C., Myaeng, S.H.: Some effective techniques for naive bayes text classification. IEEE Trans. Knowl. Data Eng. 18(11), 1457–1466 (2006)CrossRef

Kolluri, N.L., Murthy, D.: CoVerifi: a COVID-19 news verification system. Online Soc. Netw. Media 22, 100123 (2021). https://doi.org/10.1016/j.osnem.2021.100123CrossRef

Pranckevičius, T., Marcinkevičius, V.: Comparison of naive bayes, random forest, decision tree, support vector machines, and logistic regression classifiers for text reviews classification. Baltic J. Mod. Comput. 5(2), 221 (2017)CrossRef

Prasetijo, A.B., Isnanto, R.R., Eridani, D., Soetrisno, Y.A.A., Arfan, M., Sofwan, A.: Hoax detection system on Indonesian news sites based on text classification using SVM and SGD. In: 2017 4th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE), pp. 45–49. IEEE (2017)

Rennie, J.D., Shih, L., Teevan, J., Karger, D.R.: Tackling the poor assumptions of naive bayes text classifiers. In: Proceedings of the 20th International Conference on Machine Learning (ICML-03), pp. 616–623 (2003)

10.

Resende, G., Messias, J., Silva, M., Almeida, J., Vasconcelos, M., Benevenuto, F.: A system for monitoring public political groups in WhatsApp. In: Proceedings of the 24th Brazilian Symposium on Multimedia and the Web, WebMedia 2018, pp. 387–390. Association for Computing Machinery, New York (2018). https://doi.org/10.1145/3243082.3264662

11.

Su, Q., Wan, M., Liu, X., Huang, C.R.: Motivations, methods and metrics of misinformation detection: an NLP perspective. Nat. Lang. Process. Res. 1, 1–13 (2020). https://doi.org/10.2991/nlpr.d.200522.001CrossRef

12.

Waterloo, S.F., Baumgartner, S.E., Peter, J., Valkenburg, P.M.: Norms of online expressions of emotion: comparing Facebook, Twitter, Instagram, and WhatsApp. New Media Soc. 20(5), 1813–1831 (2018)CrossRef

Title: Detection of Misinformation About COVID-19 in Brazilian Portuguese WhatsApp Messages
Authors: Antônio Diogo Forte Martins
Lucas Cabral
Pedro Jorge Chaves Mourão
José Maria Monteiro
Javam Machado
Publisher: Springer International Publishing
Book: Natural Language Processing and Information Systems
Print ISBN: 978-3-030-80598-2

Electronic ISBN: 978-3-030-80599-9

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-80599-9_18

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