Predicting the virality of fake news at the early stage of dissemination Articles uri icon

publication date

  • August 2024

start page

  • 1

end page

  • 12

volume

  • 248

International Standard Serial Number (ISSN)

  • 0957-4174

Electronic International Standard Serial Number (EISSN)

  • 1873-6793

abstract

  • Fake news about brands and companies can cause reputation and financial damage, but there exist preventive strategies that could be implemented if we were able to early predict the virality of fake news pieces. In this paper, we consider the early prediction of fake news virality using textual information (body and headlines). We show that the impact of content features on virality is different for true and fake news, and so the propagation of true and fake news is. Furthermore, we use machine learning nonparametric models to classify fake news according to its propagation level. We also discuss defensive response strategies.

subjects

  • Business
  • Economics

keywords

  • fake news; machine learning; text analysis; random forest; svc classifier