Paper Title
Harnessing Bert Base Model for Effective Fake News Detection

Abstract
In today’s digital environment, the dissemination of mis- leading information poses a severe danger to the legitimacy of public discourse and information delivery. In this age of social media and om- nipresent connectivity, misinformation travels fast and has an impact on social unity, public opinion, and political processes. To overcome this is- sue, creative approaches that make use of cutting-edge technologies like machine learning and natural language processing (NLP) are required. In the area of detection of false news, Bidirectional Encoder Represen- tations from Transformers (BERT) proves to be a powerful tool. By utilising its transformer architecture and pre-training on large amounts of textual data, BERT demonstrates a deep understanding of complex language environments, which makes it easier to detect false narratives. Keywords - Fake News Detection • Natural Language Processing • BERT Model.