Fake News Detection Using Machine Learning

EasyChair Preprint 7600

Abstract

The rising popularity of social media platforms such as Facebook, Twitter, Instagram, and electronic newspapers has accelerated the propagation of fake news. With the present use of such social networks, individuals are disseminating more disinformation than ever before, the most majority of which have no basis in truth. Differentiating between authentic and fraudulent news becomes tough in this situation. In this paper, we offer a methodology for classifying news articles that incorporates natural language processing and machine learning methods. To assess the correctness of the new article, the suggested model employs a variety of vectorizers and classifiers. We want to give the user the option of classifying news as fake or true.

Keyphrases: Accuracy, Classifiers, Natural Language Processing, Vectorizers, cyberspace, fake news, machine learning

@booklet{EasyChair:7600,
  author    = {Deshmukh Akshata and Ingale Sushmita and Mani Chandan and Nair Akshaya},
  title     = {Fake News Detection Using Machine Learning},
  howpublished = {EasyChair Preprint 7600},
  year      = {EasyChair, 2022}}