Identifying Brazilian Misinformation Websites
Abstract
In this work, we propose a methodology to identify websites responsible for creating and disseminating misinformation on digital platforms in the Brazilian context. We apply our approach on Twitter. Preliminary results present evidence on the efficacy of the proposed methodology to identify misinformation websites what can be helpful in understanding this phenomenon and allow public organizations to contain the problem in different contexts.
Keywords:
Misinformation, Websites, Digital Platforms, Social media, Twitter, Fake News
References
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Bessi, A. and Ferrara, E. (2016). Social bots distort the 2016 us presidential election online discussion. First monday, 21(11-7).
Bovet, A. and Makse, H. A. (2019). Influence of fake news in twitter during the 2016 us presidential election. Nature communications, 10(1):7.
Bozarth, L. and Budak, C. (2021). Market forces: Quantifying the role of top credible ad servers in the fake news ecosystem. In Proc. of the Int’lAAAI Conf. on Web. and Soc. Med. (ICWSM), pages 83-94.
Galhardi, C. P., Freire, N. P., Minayo, M. C. d. S., and Fagundes, M. C. M. (2020). Fato ou fake? uma análise da desinformação frente à pandemia da covid-19 no Brasil. Ciência & Saúde Coletiva, 25:4201-4210.
Martins, A. D. F., Monteiro, J. M., and Machado, J. (2021). Automatic misinformation detection about covid-19 in brazilian portuguese whatsapp messages. In Proc. of the Brazilian Symposium on Data Bases (SBBD), pages 120-126.
Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L., Recchia, G., Van Der Bles, A. M., and Van Der Linden, S. (2020). Susceptibility to misinformation about covid-19 around the world. Royal Society open science, 7(10):201199.
Sharma, K., Qian, F., Jiang, H., Ruchansky, N., Zhang, M., and Liu, Y. (2019). Combating fake news: A survey on identification and mitigation techniques. ACM Transactions on Intelligent Systems and Technology (TIST), 10(3):1-42.
Bessi, A. and Ferrara, E. (2016). Social bots distort the 2016 us presidential election online discussion. First monday, 21(11-7).
Bovet, A. and Makse, H. A. (2019). Influence of fake news in twitter during the 2016 us presidential election. Nature communications, 10(1):7.
Bozarth, L. and Budak, C. (2021). Market forces: Quantifying the role of top credible ad servers in the fake news ecosystem. In Proc. of the Int’lAAAI Conf. on Web. and Soc. Med. (ICWSM), pages 83-94.
Galhardi, C. P., Freire, N. P., Minayo, M. C. d. S., and Fagundes, M. C. M. (2020). Fato ou fake? uma análise da desinformação frente à pandemia da covid-19 no Brasil. Ciência & Saúde Coletiva, 25:4201-4210.
Martins, A. D. F., Monteiro, J. M., and Machado, J. (2021). Automatic misinformation detection about covid-19 in brazilian portuguese whatsapp messages. In Proc. of the Brazilian Symposium on Data Bases (SBBD), pages 120-126.
Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L., Recchia, G., Van Der Bles, A. M., and Van Der Linden, S. (2020). Susceptibility to misinformation about covid-19 around the world. Royal Society open science, 7(10):201199.
Sharma, K., Qian, F., Jiang, H., Ruchansky, N., Zhang, M., and Liu, Y. (2019). Combating fake news: A survey on identification and mitigation techniques. ACM Transactions on Intelligent Systems and Technology (TIST), 10(3):1-42.
Published
2022-09-19
How to Cite
ARAÚJO, Leandro; NERY, Luiz Felipe; RODRIGUES, Isadora C.; COUTO, João M. M.; REIS, Julio C. S.; C. SILVA, Ana P.; ALMEIDA, Jussara M.; BENEVENUTO, Fabrício.
Identifying Brazilian Misinformation Websites. In: BRAZILIAN SYMPOSIUM ON DATABASES (SBBD), 37. , 2022, Búzios.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 355-360.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2022.225351.
