| Texto completo | |
| Autor(es): |
de Oliveira, Nicollas R.
[1]
;
Pisa, Pedro S.
[2]
;
Lopez, Martin Andreoni
[3]
;
de Medeiros, Dianne Scherly V.
[1]
;
Mattos, Diogo M. F.
[1]
Número total de Autores: 5
|
| Afiliação do(s) autor(es): | [1] Univ Fed Fluminense UFF, LabGen MidiaCom PPGEET TCE IC UFF, BR-24210240 Niteroi, RJ - Brazil
[2] Solvimm, BR-20090902 Rio De Janeiro - Brazil
[3] Technol Innovat Inst, Abu Dhabi 9639 - U Arab Emirates
Número total de Afiliações: 3
|
| Tipo de documento: | Artigo de Revisão |
| Fonte: | INFORMATION; v. 12, n. 1 JAN 2021. |
| Citações Web of Science: | 0 |
| Resumo | |
The epidemic spread of fake news is a side effect of the expansion of social networks to circulate news, in contrast to traditional mass media such as newspapers, magazines, radio, and television. Human inefficiency to distinguish between true and false facts exposes fake news as a threat to logical truth, democracy, journalism, and credibility in government institutions. In this paper, we survey methods for preprocessing data in natural language, vectorization, dimensionality reduction, machine learning, and quality assessment of information retrieval. We also contextualize the identification of fake news, and we discuss research initiatives and opportunities. (AU) | |
| Processo FAPESP: | 18/23062-5 - MEGACHAIN: blockchain para integração, privacidade e auditoria de sistemas de megacidades |
| Beneficiário: | Célio Vinicius Neves de Albuquerque |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |