Fake News Detection Using Machine Learning

Author:

Sushmitha P.

Abstract

Abstract: The advent of the World Wide Web, along with the rapid adoption of social networks such as Twitter and Facebook, paved the way for unprecedented information dissemination in human history. Consumers often create or exchange data on social networking sites, some of which are inaccurate and have no real impact. It is difficult to use algorithms to classify written works as misleading or ignorant. Even experts in this field need to consider several factors before determining the accuracy of the subject. We recommend using the ML integration method to categorize automatic news articles for this project. Our research explores various language features that can be used to distinguish between artificial and real content. Use these functions to train and test various ML algorithms on a real database. Our proposed approach to student integration outperformed individual learning in the evaluation process.

Publisher

International Journal for Research in Applied Science and Engineering Technology (IJRASET)

Subject

General Earth and Planetary Sciences,General Environmental Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Deep Convolutional Neural Networks are used to Detect Cyberbullying on Social Networks.;2023 4th IEEE Global Conference for Advancement in Technology (GCAT);2023-10-06

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