AUTOMATA: Um Ambiente para Combate Automático de Fake News em Redes Sociais Virtuais

• Augusto José M. da Fonseca CEFET-RJ
• Carlos Henrique da S. Moreira UniSãoJosé
• Gabriel Resende Machado PUC-Rio
• Paulo Márcio Souza Freire IME
• Ronaldo Ribeiro Goldschmidt IME

DOI: https://doi.org/10.5753/webmedia_estendido.2022.226555

Resumo

The propagation of fake news on social media has been increasing significantly in the last years. Despite the existence of applications that aim at suppressing the proliferation of fake news written in Portuguese, it was noticed the proposed solutions present a passive behavior regarding two aspects: (i) they are limited to identifying potential fake news only from content introduced by their users, as well as (ii) the absence of any procedures to combat disinformation. Therefore, this article presents AUTOMATA, an automated tool for combating fake news written in Portuguese. AUTOMATA periodically monitors posts made on social media and relies on Artificial Intelligence to detect suspicious fake news. After the detection process, AUTOMATA adopts a two-pronged approach to autonomously mitigate the widespread of this content, either by emitting posts on social media for warning about potential fake news or by sending the detected content to be curated by fact-checking agencies. This article also reports an experience in partnership with Ministério da Saúde for the application of AUTOMATA in the context of the COVID-19 pandemic in Brazil.

Palavras-chave: Fake News, Disinformation, Artificial Intelligence, Classification, Fake News Detection

Referências

N. J. Conroy, V. L. RFubin, and Y. Chen. 2015. Automatic Deception Detection: Methods for Finding Fake News. Assoc. Information Science and Technology 52. https://doi.org/10.1002/pra2.2015.145052010082

P. Freire et al. 2021. Fake news detection based on explicit and implicit signals of a hybrid crowd. Expert Systems with Applications 183 (2021). https://doi.org/10.1016/j.eswa.2021.115414

P. Freire and R. Goldschmidt. 2019. Fake News Detection on Social Media via Implicit Crowd Signals. In Proc. of the 25th WebMedia (Rio de Janeiro, Brazil). ACM, New York, NY, USA, 521–524. https://doi.org/10.1145/3323503.3360626

P. Freire and R. Goldschmidt. 2020. Combatendo Fake News nas Redes Sociais via Crowd Signals Implícitos. In Anais do XVI ENIAC. SBC, Porto Alegre, RS, 424–435. https://doi.org/10.5753/eniac.2019.9303

Y. Mejova and K. Kalimeri. 2020. Advertisers Jump on Coronavirus Bandwagon: Politics, News, and Business. ArXiv abs/2003.00923 (2020).

K. Shu, A. Silva, S. Wang, J. Tang, and H. Liu. 2017. Fake News Detection on Social Media: A Data Mining Perspective. ACM SIGKDD Explorations Newsletter 19, 1, 22–36. https://doi.org/10.1145/3137597.3137600