Authors: Durga Prasad, Dr. Avadhesh Kumar Dixit
Abstract: The spread of fake news and misinformation on the internet has becoming the very serious problem, which making it difficult for the people to know what to trust. The current methods for verifying news often have the limitations: they can be too slow, lack transparency, or fail to confirm that the original source of story. This paper is proposing a new system that is combining two powerful technologies to addressing these challenges. Where first, we use the text analysis techniques from the field of Natural Language Processing (NLP) to scan news contents and identifying linguistic patterns often associated with the false and misleading information. Second, we leveraging the blockchain technology which is used to create a tamper-proof record of a news article’s origin and any changes made to it over time. By storing a digital footprint of the verified content on the blockchain, our system which allowing the readers to check if the news they are viewing matches the original version published by a trusted source. This dual-prolonged approach not only helps flag the potentially deceptive content through analysis but also builds a trustworthy chain of provenance. In the proposed system offers a more reliable and transparent way to verify digital news, empowering users to make informed judgments about the information they will consume.
DOI: http://doi.org/10.5281/zenodo.21333813
