FAKE NEWS DETECTION USING BERT(NLP)

Abstract

The increase of fake news poses an important concern in today's information-rich environment age, prompting the exploration of advanced techniques for detection and mitigation. Among these techniques, BERT (Bidirectional Encoder Representations from Transformers) has emerged as a potent, robust and mighty tool, particularly in the field of natural language processing. The primary objective of incorporating BERT into fake news detection is to elevate the precision and efficiency of discerning misleading information, thereby safeguarding the credibility of information dissemination.

In summary, the integration of the BERT technique in fake news detection manages the escalating challenges posed by deceptive information dissemination. Its primary objective is to enhance the precision of detection methods, addressing the pressing need for sophisticated tools in light of the evolving landscape of deceptive practices. The application of BERT extends across various platforms, contributing to the creation of a more secure and reliable information landscape in the digital age.