Fake News Detection Using Blockchain

EasyChair Preprint no. 10323

Abstract

Social media networks have emerged as an essential component of human existence as a result of recent technological advancements in computing era. This climate has turned into a notable stage for trading data and news on various topics, as well as day to day reports, and it is the essential time frame for information assortment and transmission. This climate enjoys many benefits, however it likewise contains a ton of fake news and data that confounds clients and per users about the data they require. The absence of real-time social media news and reliable information is a major concern for the system. We suggested a machine learning-based integrated solution that would better anticipate bogus user accounts and postings and identify false news for multiple blockchain components using natural language processing (NLP). The proposed methodology utilizes the Support Learning procedure and decentralized blockchain architecture, which gives an outline of computerized content power verification to improve the stage's security. The target of this framework is to offer a solid strategy for foreseeing and distinguishing fake news via social media stages

Keyphrases: Blockchain, Fake media, Natural Language Processing, Reinforcement Learning

@Booklet{EasyChair:10323,
  author = {Veetu Kaushik and Taslim Raza Ahmad and Jai Sanger and Renu Mishra},
  title = {Fake News Detection Using Blockchain},
  howpublished = {EasyChair Preprint no. 10323},

  year = {EasyChair, 2023}}