Fake News and Brazilian politics – temporal investigation based on semantic annotations and graph analysis
Resumo
The widespread use of misleading news articles has been threatening democratic processes such as elections and referendums. Understanding how fake news address social entities (e.g. personalities and institutions) and how they react to social events are important factors in the fight against the trend. This paper employs a new approach based on semantic annotations and graph analysis to study fake news articles about Brazilian politics in a two-year time span. We demonstrate how graph analysis can be used to track topic evolution and cluster related entities. A preliminary result also indicates that fake news tends to be influenced by public interest (and not the other way around).
Palavras-chave:
Temporal investigation, semantic annotations, graph analysis, fake news
Referências
Allcott, H. and Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2):211–36. DOI: https://doi.org/10.3386/w23089
da F. Costa, L., Rodrigues, F. A., Travieso, G., and Boas, P. R. V. (2007). Characterization of complex networks: A survey of measurements. Advances in Physics, 56(1):167–242. DOI: https://doi.org/10.1080/00018730601170527
Jang, S. M., Geng, T., Li, J.-Y. Q., Xia, R., Huang, C.-T., Kim, H., and Tang, J. (2018). A computational approach for examining the roots and spreading patterns of fake news: Evolution tree analysis. Computers in Human Behavior, 84:103–113. DOI: https://doi.org/10.1016/j.chb.2018.02.032
Mendes, P. N., Jakob, M., Garc´ıa-Silva, A., and Bizer, C. (2011). Dbpedia spotlight: Shedding light on the web of documents. In Proceedings of the 7th International Conference on Semantic Systems. ACM. DOI: https://doi.org/10.1145/2063518.2063519
Monteiro, R. A., Santos, R. L. S., Pardo, T. A. S., de Almeida, T. A., Ruiz, E. E. S., and Vale, O. A. (2018). Contributions to the study of fake news in portuguese: New corpus and automatic detection results. In Computational Processing of the Portuguese Language, pages 324–334. Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-99722-3_33
da F. Costa, L., Rodrigues, F. A., Travieso, G., and Boas, P. R. V. (2007). Characterization of complex networks: A survey of measurements. Advances in Physics, 56(1):167–242. DOI: https://doi.org/10.1080/00018730601170527
Jang, S. M., Geng, T., Li, J.-Y. Q., Xia, R., Huang, C.-T., Kim, H., and Tang, J. (2018). A computational approach for examining the roots and spreading patterns of fake news: Evolution tree analysis. Computers in Human Behavior, 84:103–113. DOI: https://doi.org/10.1016/j.chb.2018.02.032
Mendes, P. N., Jakob, M., Garc´ıa-Silva, A., and Bizer, C. (2011). Dbpedia spotlight: Shedding light on the web of documents. In Proceedings of the 7th International Conference on Semantic Systems. ACM. DOI: https://doi.org/10.1145/2063518.2063519
Monteiro, R. A., Santos, R. L. S., Pardo, T. A. S., de Almeida, T. A., Ruiz, E. E. S., and Vale, O. A. (2018). Contributions to the study of fake news in portuguese: New corpus and automatic detection results. In Computational Processing of the Portuguese Language, pages 324–334. Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-99722-3_33
Publicado
07/10/2019
Como Citar
GOMES JR., Luiz; FRIZZON, Gabriel.
Fake News and Brazilian politics – temporal investigation based on semantic annotations and graph analysis. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 34. , 2019, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 169-174.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2019.8818.
