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