Are You Influenced?: Modeling the Diffusion of Fake News in Social Media

Abishai Joy, Anu Shrestha, Francesca Spezzano

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We propose an approach inspired by the diffusion of innovations theory to model and characterize fake news sharing in social media through the lens of the different levels of influential factors (users, networks, and news). We address the problem of predicting fake news sharing as a classification task and demonstrate the potentials of the proposed features by achieving an AUROC of 0.97 and an average precision of 0.88, consistently outperforming baseline models with a higher margin (about 30% of AUROC). Also, we show that news-based features are the most effective at predicting real and fake news sharing, followed by the user- and network-based features.

Original languageAmerican English
Title of host publicationASONAM '21: Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
StatePublished - 1 Nov 2021

Keywords

  • diffusion of innovations theory
  • fake news sharing
  • information diffusion
  • misinformation

EGS Disciplines

  • Computer Sciences

Fingerprint

Dive into the research topics of 'Are You Influenced?: Modeling the Diffusion of Fake News in Social Media'. Together they form a unique fingerprint.

Cite this