Title: Fake news detection system using stance detection and machine learning approaches
Authors: Akhilesh Kumar Srivastava; Rijwan Khan
Addresses: ABES Engineering College, Ghaziabad, India ' ABES Institute of Technology, Ghaziabad, India
Abstract: In the present internet era, a need for genuine news sources is in high demand. With increased expansion and reachability of internet service, the consumption of news has seen a major growth. This growth has led to creation of different sources of news and has bought a revolution in the way the news is consumed and this heterogeneity has led to decline in authenticity of the news delivered and respective news sources. In this paper, authors glance over different present approaches in the direction of detecting fake news and discuss a stance-based method to review a claim and decide if its 'REAL' or 'FAKE'.
Keywords: fake news detection; stance detection; machine learning; deception; Boolean crowdsourcing algorithms; BCA.
DOI: 10.1504/IJFSE.2022.123982
International Journal of Forensic Software Engineering, 2022 Vol.1 No.4, pp.378 - 389
Received: 08 Aug 2021
Accepted: 01 Apr 2022
Published online: 05 Jul 2022 *