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Journal of Information and Optimization Sciences cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Open Access Research Article

FakeSpotter: A blockchain-based trustworthy idea for fake news detection in social media

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pp. 515–527Vol. 44Issue 3April 2023DOI: 10.47974/JIOS-1411XML
Published Online:
11 Aug 2023
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1411
Pages:
515–527

Abstract

Social media encourages information sharing without a physical barrier making it the perfect platform for learning and communication. In the meantime, it acts as a means of quickly disseminating misleading information. Researchers are battling fake news using strategies like detection, verification, mitigation, and analysis because of significant social concerns. It can be hard to tell the difference between true and false information. In the area of knowledge verification, various machine and deep learning-based approaches have been used to identify false data. However, there are some drawbacks of using AI-powered technologies, including data dependency, security concerns when applying AI-powered methods in the real world, and gaining user trust. In order to address the issues with AI-powered technologies, a blockchain-based idea (FakeSpotter) is put forth in this work. We offer an idea i.e.based on blockchain that utilizes crowdsourcing to determine whether or not content is fake. We attempt to use Blockchain technology’s features correctly and completely to create a secure system with no authoritative control over information dissemination. In this attempt, we aim to build a system that is not reliant on pre-defined datasets and discuss the initiatives taken in the fight against disinformation.

Keywords

Subject Classifications

68T50

References

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