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English Information

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Authors
# Name
1 João Couto(joaocouto@dcc.ufmg.br)
2 Isadora Salles(isadorasalles@dcc.ufmg.br)
3 Breno C. Pimenta(brenopimenta@dcc.ufmg.br)
4 Samuel Assis(samuelassis@dcc.ufmg.br)
5 Leandro Silva( leandroaraujo@dcc.ufmg.br)
6 Julio dos Reis(jreis@ufv.br)
7 Fabricio Benevenuto(fabricio@dcc.ufmg.br)

(*) To change the order drag the item to the new position.

Reference
# Reference
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2 Breiman, L., Friedman, J. H., Olshen, R. A., and Stone, C. J. (2017). Classification and regression trees. Routledge
3 Charles, A. C., Ruback, L., and Oliveira, J. (2022). Fakepedia corpus: A flexible fake news corpus in portuguese. In Proc. of the Int’l Conference on Computational Processing of the Portuguese Language, pages 37-45.
4 Chen, T. and Guestrin, C. (2016). Xgboost: A scalable tree boosting system. In Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining, pages 785–794.
5 Conroy, N. K., Rubin, V. L., and Chen, Y. (2015). Automatic deception detection: Methods for finding fake news. Proc. of the Association for Information Science and Technology, pages 1–4
6 Couto, J. M. M., Pimenta, B., de Araújo, I. M., Assis, S., Reis, J. C., da Silva, A. P. C., Almeida, J. M., and Benevenuto, F. (2021). Central de fatos: Um repositório de checagens de fatos. In Proc. of the Dataset Showcase Workshop (DSW), pages 128–137.
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11 Martins, A. D. F., Cabral, L., Mourao, P. J. C., Monteiro, J. M., and Machado, J. (2021). Detection of misinformation about covid-19 in brazilian portuguese whatsapp messages using deep learning. In Proc. of the Brazilian Symposium on Databases (SBBD), pages 85–96.
12 Massarani, L. M., Leal, T., Waltz, I., and Medeiros, A. (2021). Infodemia, desinformação e vacinas: a circulação de conteúdos em redes sociais antes e depois da covid-19. Liincem Revista, 17(1):e5689.
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16 Reis, J. C., Correia, A., Murai, F., Veloso, A., and Benevenuto, F. (2019b). Supervised learning for fake news detection. IEEE Intelligent Systems, 34(2):76–81
17 Reis, J. C., Melo, P., Garimella, K., Almeida, J. M., Eckles, D., and Benevenuto, F. (2020). A dataset of fact-checked images shared on whatsapp during the brazilian and indian elections. In Proc. of the Int’l AAAI Conference on Weblogs and Social Media, pages 903–908.
18 Reis, J. C. S., de Souza, F., Vaz de Melo, P., Prates, R., Kwak, H., and An, J. (2015). Breaking the news: First impressions matter on online news. In Proc. of the Int’l AAAI Conference on Web and Social Media, pages 357–366
19 Ribeiro, F. N., Saha, K., Babaei, M., Henrique, L., Messias, J., Benevenuto, F., Oana Goga, K. P. G., and Redmiles, E. M. (2019). On microtargeting socially divisive ads: A case study of russia-linked ad campaigns on facebook. In Proc. of the ACM Conference on Fairness, Accountability, and Transparency.
20 Shu, K., Sliva, A., Wang, S., Tang, J., and Liu, H. (2017). Fake news detection on social media: A data mining perspective. ACM SIGKDD explorations newsletter, 19(1):22–36.
21 Tausczik, Y. R. and Pennebaker, J. W. (2010). The psychological meaning of words: Liwc and computerized text analysis methods. Journal of Language and Social Psychology, 29(1):24–54.
22 Vargas, F., D ́Alessandro, J., Rabinovich, Z., Benevenuto, F., and Pardo, T. A. (2022). Rhetorical structure approach for online deception detection: A survey. In Proc. of the Int’l Conference on Language Resources and Evaluation, pages 357–366
23 Volkova, S., Shaffer, K., Jang, J. Y., and Hodas, N. (2017). Separating facts from fiction: Linguistic models to classify suspicious and trusted news posts on twitter. In Proc. of the Annual Meeting of the Association for Computational Linguistics, pages 647–653
24 Vosoughi, S., Roy, D., and Aral, S. (2018). The spread of true and false news online. Science, 359(6380):1146–1151.
25 White, T. E. and Rege, M. (2020). Sentiment analysis on google cloud platform. Issues in Information Systems, 21(2):221–228.