Work

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

Year: 2021

Type: article

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.

Source: Information

DOI: 10.3390/info12010038

Authors: Nicollas R. de Oliveira, Pedro S. Pisa, Martin Andreoni Lopez, Dianne Scherly V. de Medeiros, Diogo M. F. Mattos

Institutions: Universidade Federal Fluminense, Technology Innovation Institute

Language: English

Topic: Misinformation and Its Impacts

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,512

Funders: Fundação de Amparo à Pesquisa do Estado de São Paulo, Conselho Nacional de Desenvolvimento Científico e Tecnológico