Fake News is the misinformation disseminated among the public by mainstream sources like media outlets and social media. It is generally misleading to shape beliefs of the masses to one's favour. There are Different approaches to identifying fake news were examined, such as content-based classification, social context-based classification, image-based classification, sentiment-based classification, and hybrid context-based classification. This project aims to propose a model for fake news classification based on news titles, following the content-based classification approach. The model uses a BERT Model and further Logistic Regression. Training and evaluation of the model were done on the FakeNewsNet dataset.
KharbandaBhavy/Big_Data_Project
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