| Full text | |
| Author(s): |
de Oliveira, Nicollas R.
[1]
;
Pisa, Pedro S.
[2]
;
Lopez, Martin Andreoni
[3]
;
de Medeiros, Dianne Scherly V.
[1]
;
Mattos, Diogo M. F.
[1]
Total Authors: 5
|
| Affiliation: | [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
Total Affiliations: 3
|
| Document type: | Review article |
| Source: | INFORMATION; v. 12, n. 1 JAN 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
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) | |
| FAPESP's process: | 18/23062-5 - MEGACHAIN: blockchain for integration, privacy and audit of megacity systems |
| Grantee: | Célio Vinicius Neves de Albuquerque |
| Support Opportunities: | Regular Research Grants |