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Novel Framework for Fake News and Scam Prediction Using NLP and Transfer Learning Model

R. SathiyaseelanArunai Engineering College,Department of CSE,Tiruvannamalai,IndiaK. YogithaArunai Engineering College,Department of ECE,Tiruvannamalai,IndiaAbdusamatov AlisherTermez University of Economics and Service,Department of Preschool and Primary Education,Termez,UzbekistanBarno MatchanovaUrgench state pedagogical institute,Department of national idea and philosophy,Urgench,UzbekistanOtajonova GulkhayoMamun university,Department of exact science,Khiva,UzbekistanB. VenkataramanaiahVel Tech Rangarajan Dr.sagunthala R&D Institute of science and technology,Department of ECE,Chennai,India

2026

ABI

Annotatsiya

Fake news plays the most dangerous role in human life. Nowadays fake news spreads more than genuine news due to social media. Another serious issue for people is scam. Cyber hackers sent messages to people to get money from bank accounts. Information can now be shared in ways never seen in human history thanks to the World Wide Web's creation and the rapid adoption of social media sites like Facebook, Instagram, and WhatsApp. The hiring pattern has shifted due to online hiring. Specifically, posting job advertisements on corporate websites and career portals entails searching a large global pool of competent applicants. Sadly, it has turned into yet another platform for con artists, endangering applicants' privacy and damaging businesses' reputations. The proposed research addresses the issue of identifying fake news and scams. Random forest, Logistic regression from Natural Language processing(NLP) and Vision Transformer(ViT) from Transfer learning used in proposed research to predict fake news and scam.

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Mavzular

Spam and Phishing Detection Misinformation and Its Impacts Internet of Things and AI

Identifikatorlar

DOI: 10.1109/icsadl67539.2026.11451847

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