Volume 17, Issue 3 (7-2025)                   itrc 2025, 17(3): 34-45 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Tafazzoli T, Arab Sorkhi A. An In-Depth Comparative Analysis of Fake News Detection Approaches in Social Media: Methodologies, Challenges, and Future Directions. itrc 2025; 17 (3) :34-45
URL: http://ijict.itrc.ac.ir/article-1-760-en.html
An In-Depth Comparative Analysis of Fake News Detection Approaches in Social Media: Methodologies, Challenges, and Future Directions
Tala Tafazzoli1 , Abouzar Arab Sorkhi2
1- ICT Research Institute (ITRC) Tehran, Iran
2- ICT Research Institute (ITRC) Tehran, Iran , abouzar_arab@itrc.ac.ir
Abstract:   (481 Views)
The proliferation of fake news on social networks poses significant challenges for trust, security, and societal well-being. In this paper, we present a comprehensive study of fake news detection approaches and techniques, introducing a novel framework for news construction comprising four elements: news content, news context, news propagation, and news environment. We propose a new taxonomy of fake news detection techniques categorized into two primary types—individual methods (content-based, context-based, and propagation-based) and frameworks (hybrid and perception-aware methods). We highlight their strengths, weaknesses, and applicability by analyzing 14 state-of-the-art detection methods across platforms such as Twitter, Facebook, and Sina-Weibo. Furthermore, we address critical research gaps by identifying future directions, including early fake news detection, unsupervised learning, multimodal datasets, adversarial attacks on algorithms, multi-lingual platforms, and AI-generated content detection. Our findings and recommendations aim to serve as a foundation for developing new robust, scalable, and impactful fake news detection systems.
Keywords: Fake news detection, Content-based methods, Context-based methods, Propagation-based methods, Hybrid methods, Perception-aware frameworks.
Full-Text [PDF 746 kb]   (158 Downloads)    
Type of Study: Research | Subject: Information Technology
Add your comments about this article : Your username or Email:
CAPTCHA
Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.