Buku Fake News Detection and Verification: Concepts, Methods, and Intelligent Systems

Penulis
Zaitul Iradah Binti Mahid
Selvakumar Manickam
Ridho Surya Kusuma
Shankar Karuppayah

Ukuran 17.5 x 25 cm
ISBN (Dalam proses)

Sinopsis Buku
In an age characterized by the unprecedented proliferation of digital misinformation, efficient and precise truth verification has emerged as a critical societal imperative. Fake News Detection: Intelligent Fact-Checking Based on Relational Similarity and Confidence Score in Knowledge Graph introduces an innovative, computationally advanced framework designed to counter false information.

The core of this work is derived from a rigorous, two-year interdisciplinary research initiative that intersects digital economics, information technology, and cybersecurity. The volume demonstrates how knowledge graphs—augmented by relational similarity metrics and confidence scoring algorithms—can drive scalable, transparent, and robust verification architectures. Beyond technical implementation, the text analyzes the theoretical foundations of disinformation, examining both its psychosocial underpinnings and its viral dissemination dynamics across digital networks.

The book comprehensively details the proposed Fake News Detection (FND) mechanism, outlining the sequential pipeline from entity alignment and evidence extraction to semantic relation validation and formal fact inference. To optimize accuracy, systemic adaptability, and model explainability, the authors integrate novel techniques such as edge capacity modeling and dynamic confidence calculation into the fact-checking workflow.

Underpinned by strong methodological principles, this monograph presents comprehensive comparative evaluations alongside current state-of-the-art algorithms, validated by empirical performance metrics on extensive benchmarking datasets including DBpedia and YAGO. Tailored for academic researchers, computer science practitioners, and policymakers, this text serves as both an intellectual cornerstone and a practical guide for counteracting misinformation within the contemporary digital ecosystem.