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TriFactNet: A Multi-Modal Neural Architecture for Fake News Detection Using Text, Source Credibility, and Stance

pread of misinformation on online platforms has made fake news detection systems more essential and demanding. TriFactNet is introduced in this study as an innovative multi-factor deep learning approach combining semantic textual features, credibility of sources, and synthetic stance vectors for improved fake news accuracy and reliability.

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