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.2022.10047949

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 *

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