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Review

Identifying Fake News on Social Networks Based on Natural Language Processing: Trends and Challenges

1
LabGen/MídiaCom–PPGEET/TCE/IC/UFF, Universidade Federal Fluminense (UFF), Niterói 24210-240, Brazil
2
Solvimm, Rio de Janeiro 20090-902, Brazil
3
Technology Innovation Institute (TII), Abu Dhabi 9639, UAE
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Information 2021, 12(1), 38; https://doi.org/10.3390/info12010038
Received: 9 December 2020 / Revised: 1 January 2021 / Accepted: 7 January 2021 / Published: 18 January 2021
(This article belongs to the Special Issue Decentralization and New Technologies for Social Media)
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. View Full-Text
Keywords: fake news; machine learning; natural language processing; social networking fake news; machine learning; natural language processing; social networking
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MDPI and ACS Style

de Oliveira, N.R.; Pisa, P.S.; Lopez, M.A.; de Medeiros, D.S.V.; Mattos, D.M.F. Identifying Fake News on Social Networks Based on Natural Language Processing: Trends and Challenges. Information 2021, 12, 38. https://doi.org/10.3390/info12010038

AMA Style

de Oliveira NR, Pisa PS, Lopez MA, de Medeiros DSV, Mattos DMF. Identifying Fake News on Social Networks Based on Natural Language Processing: Trends and Challenges. Information. 2021; 12(1):38. https://doi.org/10.3390/info12010038

Chicago/Turabian Style

de Oliveira, Nicollas R., Pedro S. Pisa, Martin A. Lopez, Dianne S.V. de Medeiros, and Diogo M.F. Mattos. 2021. "Identifying Fake News on Social Networks Based on Natural Language Processing: Trends and Challenges" Information 12, no. 1: 38. https://doi.org/10.3390/info12010038

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