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English Information

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Authors
# Name
1 Antônio Diogo Martins(diogo.martins@lsbd.ufc.br)
2 José Monteiro(jose.monteiro@lsbd.ufc.br)
3 Javam Machado(javam.machado@lsbd.ufc.br)

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Reference
# Reference
1 Choudrie, J., Banerjee, S., Kotecha, K., Walambe, R., Karende, H., and Ameta, J. (2021). Machine learning techniques and older adults processing of online information and misinformation: A covid 19 study. Computers in Human Behavior, 119:106716.
2 Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.
3 Elhadad, M. K., Li, K. F., and Gebali, F. (2020). Detecting misleading information on covid-19. IEEE Access, 8:165201–165215.
4 Garimella, K. and Tyson, G. (2018). Whatsapp, doc? a first look at whatsapp public group data. arXiv preprint arXiv:1804.01473.
5 Giachanou, A., Zhang, G., and Rosso, P. (2020). Multimodal multi-image fake news detection. In 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), pages 647–654.
6 Hochreiter, S. and Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8):1735–1780.
7 Kim, S.-B., Han, K.-S., Rim, H.-C., and Myaeng, S. H. (2006). Some effective techniques for naive bayes text classification. IEEE transactions on knowledge and data engineering, 18(11):1457–1466.
8 Kolluri, N. L. and Murthy, D. (2021). Coverifi: A covid-19 news verification system. Online Social Networks and Media, 22:100123.
9 Martins, A. D. F., Cabral, L., Chaves Mourao, P. J., Monteiro, J. M., and Machado, J. (2021). Detection of misinformation about covid-19 in brazilian portuguese whatsapp messages. In Metais, E., Meziane, F., Horacek, H., and Kapetanios, E., editors, Natural Language Processing and Information Systems, pages 199–206, Cham. Springer International Publishing.
10 Pranckevicius, T. and Marcinkevicius, V. (2017). Comparison of naive bayes, random forest, decision tree, support vector machines, and logistic regression classifiers for text reviews classification. Baltic Journal of Modern Computing, 5(2):221.
11 Prasetijo, A. B., Isnanto, R. R., Eridani, D., Soetrisno, Y. A. A., Arfan, M., and Sofwan, A. (2017). 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), pages 45–49. IEEE.
12 Rennie, J. D., Shih, L., Teevan, J., and Karger, D. R. (2003). Tackling the poor assumptions of naive bayes text classifiers. In Proceedings of the 20th international conference on machine learning (ICML-03), pages 616–623.
13 Resende, G., Messias, J., Silva, M., Almeida, J., Vasconcelos, M., and Benevenuto, F. (2018). A system for monitoring public political groups in whatsapp. In Proceedings of the 24th Brazilian Symposium on Multimedia and the Web, WebMedia ’18, page 387–390, New York, NY, USA. Association for Computing Machinery.
14 Su, Q., Wan, M., Liu, X., and Huang, C.-R. (2020). Motivations, methods and metrics of misinformation detection: An nlp perspective. Natural Language Processing Research, 1:1–13.
15 Waterloo, S. F., Baumgartner, S. E., Peter, J., and Valkenburg, P. M. (2018). Norms of online expressions of emotion: Comparing facebook, twitter, instagram, and whatsapp. new media & society, 20(5):1813–1831.