ReVera Framework: Um Framwork para rastreabilidade em fact-checking automático
Resumo
A verificação manual de fatos tende a ser cara e a escalabilidade desafiadora, incentivando a busca por métodos automáticos. Porém, esses métodos foram criados com arquiteturas monolíticas, não fazendo uso de peças pré-construídas e são mais difíceis de serem compreendidos por terceiros. Este trabalho tem como objetivo propor um framework, onde o desenvolvimento de métodos pode ser feito de forma modular, criando fluxos de trabalho baseados em etapas-chave que podem ser interligadas para gerar a classificação de entrada. O framework faz uso de uma ontologia de rastreabilidade proposta para mapear todos os dados gerados durante a execução sob um vocabulário unificado, o que facilita a comunicação entre esses componentes independentes.
Referências
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Conroy, N. J., Rubin, V. L., and Chen, Y. (2015). Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Science and Technology, 52(1):1–4.
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Hassan, N., Adair, B., Hamilton, J., Li, C., Tremayne, M., Yang, J., and Yu, C. (2015). The quest to automate fact-checking. Proceedings of the 2015 Computation + Journalism Symposium.
Hassan, N., Zhang, G., Arslan, F., Caraballo, J., Jimenez, D., Gawsane, S., Hasan, S., Joseph, M., Kulkarni, A., Nayak, A. K., Sable, V., Li, C., and Tremayne, M. (2017). Claimbuster: The first-ever end-to-end fact-checking system. Proc. VLDB Endow., 10(12):1945–1948.
Kotonya, N. and Toni, F. (2020). Explainable automated fact-checking for public health claims.
Mendonça, F. M., de Castro, L. P., de Souza, J. F., Almeida, M. B., and Felipe, E. R. (2020). Onto4alleditor: um editor web gráfico de ontologias direcionado a diferentes tipos de desenvolvedores de ontologias. Proceedings of the XIII Seminar on Ontology Research in Brazil and IV Doctoral and Masters Consortium on Ontologies (ONTOBRAS 2020).
Miranda, S., Nogueira, D., Mendes, A., Vlachos, A., Secker, A., Garrett, R., Mitchell, J., and Marinho, Z. (2019). Automated fact checking in the news room. CoRR, abs/1904.02037.
Munir, K. and Sheraz Anjum, M. (2018). The use of ontologies for effective knowledge modelling and information retrieval. Applied Computing and Informatics, 14(2):116–126.
Nadeem, M., Fang, W., Xu, B., Mohtarami, M., and Glass, J. (2019). Fakta: An automatic end-to-end fact checking system.
Rehm, G., Schneider, J. M., and Bourgonje, P. (2018). Automatic and manual web annotations in an infrastructure to handle fake news and other online media phenomena. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).
Santos, R. and Pardo, T. (2020). Fact-Checking for Portuguese: Knowledge Graph and Google Search-Based Methods, pages 195–205.
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.
Souza, J., Gomes Jr, J., Marques, F., Julio, A., and Souza, J. (2020). A systematic mapping on automatic classification of fake news in social media. Social Network Analysis and Mining, 10.
Volodina, E., Borin, L., Loftsson, H., Arnbjörnsdóttir, B., and Leifsson, G. Ö. (2012). Waste not, want not: Towards a system architecture for icall based on nlp component re-use. volume 80, pages 47–58.
Bittner, T., Donnelly, M., and Winter, S. (2006). Ontology and semantic interoperability.
Both, A., Diefenbach, D., Singh, K., Shekarpour, S., Cherix, D., and Lange, C. (2016). Qanary - a methodology for vocabulary-driven open question answering systems. In Proceedings of the 13th International Conference on The Semantic Web. Latest Advances and New Domains Volume 9678, page 625–641, Berlin, Heidelberg. SpringerVerlag.
Conroy, N. J., Rubin, V. L., and Chen, Y. (2015). Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Science and Technology, 52(1):1–4.
da Silva, F. R. M., Freire, P. M. S., de Souza, M. P., de A. B. Plenamente, G., and Goldschmidt, R. R. (2020). Fakenewssetgen: A process to build datasets that support comparison among fake news detection methods. In Proceedings of the Brazilian Symposium on Multimedia and the Web, WebMedia ’20, page 241–248, New York, NY, USA. Association for Computing Machinery.
Gerber, D., Esteves, D., Lehmann, J., Bühmann, L., Usbeck, R., Ngonga Ngomo, A.-C., and Speck, R. (2015). Defacto temporal and multilingual deep fact validation. Web Semantics: Science, Services and Agents on the World Wide Web.
Graves, D. (2018). Understanding the promise and limits of automated fact-checking.
Hassan, N., Adair, B., Hamilton, J., Li, C., Tremayne, M., Yang, J., and Yu, C. (2015). The quest to automate fact-checking. Proceedings of the 2015 Computation + Journalism Symposium.
Hassan, N., Zhang, G., Arslan, F., Caraballo, J., Jimenez, D., Gawsane, S., Hasan, S., Joseph, M., Kulkarni, A., Nayak, A. K., Sable, V., Li, C., and Tremayne, M. (2017). Claimbuster: The first-ever end-to-end fact-checking system. Proc. VLDB Endow., 10(12):1945–1948.
Kotonya, N. and Toni, F. (2020). Explainable automated fact-checking for public health claims.
Mendonça, F. M., de Castro, L. P., de Souza, J. F., Almeida, M. B., and Felipe, E. R. (2020). Onto4alleditor: um editor web gráfico de ontologias direcionado a diferentes tipos de desenvolvedores de ontologias. Proceedings of the XIII Seminar on Ontology Research in Brazil and IV Doctoral and Masters Consortium on Ontologies (ONTOBRAS 2020).
Miranda, S., Nogueira, D., Mendes, A., Vlachos, A., Secker, A., Garrett, R., Mitchell, J., and Marinho, Z. (2019). Automated fact checking in the news room. CoRR, abs/1904.02037.
Munir, K. and Sheraz Anjum, M. (2018). The use of ontologies for effective knowledge modelling and information retrieval. Applied Computing and Informatics, 14(2):116–126.
Nadeem, M., Fang, W., Xu, B., Mohtarami, M., and Glass, J. (2019). Fakta: An automatic end-to-end fact checking system.
Rehm, G., Schneider, J. M., and Bourgonje, P. (2018). Automatic and manual web annotations in an infrastructure to handle fake news and other online media phenomena. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).
Santos, R. and Pardo, T. (2020). Fact-Checking for Portuguese: Knowledge Graph and Google Search-Based Methods, pages 195–205.
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.
Souza, J., Gomes Jr, J., Marques, F., Julio, A., and Souza, J. (2020). A systematic mapping on automatic classification of fake news in social media. Social Network Analysis and Mining, 10.
Volodina, E., Borin, L., Loftsson, H., Arnbjörnsdóttir, B., and Leifsson, G. Ö. (2012). Waste not, want not: Towards a system architecture for icall based on nlp component re-use. volume 80, pages 47–58.
Publicado
29/11/2021
Como Citar
SOUZA, João Victor de; ASSIS, Elias Cyrino de; MENDONÇA, Fabrício Martins; SOUZA, Jairo Francisco de.
ReVera Framework: Um Framwork para rastreabilidade em fact-checking automático. In: SIMPÓSIO BRASILEIRO DE TECNOLOGIA DA INFORMAÇÃO E DA LINGUAGEM HUMANA (STIL), 13. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 209-216.
DOI: https://doi.org/10.5753/stil.2021.17800.
