Linguistic-Based Detection of Fake News in Social Media

Forthcoming, International Journal of English Linguistics, Vol. 11, No. 1, DOI:10.5539/ijel.v11n1p99

11 Pages Posted: 3 Dec 2020

See all articles by Mohammad Mahyoob

Mohammad Mahyoob

Taibah University

Jeehaan Al-Garaady

Taiz University

Musaad Alrahaili

affiliation not provided to SSRN

Date Written: 2020

Abstract

The tremendous growth and impact of fake news as a hot research field gained the public’s attention and threatened their safety in recent years. However, there is a wide range of developed fashions to detect fake contents, either those human-based approaches or machine-based approaches; both have shown inadequacy and limitations, especially those fully automatic approaches. The purpose of this analytic study of media news language is to investigate and identify the linguistic features and their contribution in analyzing data to detect, filter, and differentiate between fake and authentic news texts. This study outlines promising uses of linguistic indicators and adds a rather unconventional outlook to prior literature. It utilizes qualitative and quantitative data analysis as an analytic method to identify systematic nuances between fake and factual news in terms of detecting and comparing 16 attributes under three main linguistic features categories (lexical, grammatical, and syntactic features) assigned manually to news texts. The obtained datasets consist of publicly available right documents on the Politi-fact website and the raw (test) data set collected randomly from news posts on Facebook pages. The results show that linguistic features, especially grammatical features, help determine untrustworthy texts and demonstrate that most of the test news tends to be unreliable articles.

Keywords: fake news detection, data mining, linguistic features, text classification, content analysis, social media

Suggested Citation

Mahyoob, Mohammad and Al-Garaady, Jeehaan and Alrahaili, Musaad, Linguistic-Based Detection of Fake News in Social Media (2020). Forthcoming, International Journal of English Linguistics, Vol. 11, No. 1, DOI:10.5539/ijel.v11n1p99, Available at SSRN: https://ssrn.com/abstract=3652758

Mohammad Mahyoob

Taibah University ( email )

Prince Naif Ibn Abdulaziz, Tayba, Medina Saudi Ara
Mediana, Madinah
Saudi Arabia

Jeehaan Al-Garaady (Contact Author)

Taiz University ( email )

Yemen

Musaad Alrahaili

affiliation not provided to SSRN

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