Novel Measures for Fake and Real News Propagation in Social Networks

Abstract

The rise of false rumors and fake news in online social networks has gained significant interest, but we currently lack the tools to fundamentally understand this problem. While some work has been carried out to assess and even categorize false rumors from real news, these methods often lack fundamental intuition and thus fail to truly explain the differences between these different types of news. Here we propose to study the differences and similarities between false rumors and real news by analyzing the network through which the information spreads. Network structure is a global feature and cannot be influenced by few individuals, therefore potentially making it more useful for distinguishing false rumors. We will focus on global and local features to create metrics rooted in sociological mechanisms. These metrics will allow, as suggested by our preliminary results, for early identification of false rumors and provide intuitive methods to prevent rumors spreading. A complementary analysis, will consider the entire rumor ecosystem and how specific users spread rumors repetitively. We will focus on repetitive users by attempting to understand their collaboration and how they leverage their connections to spread false rumors.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 14, 2019
Source ID
W911NF1810396

Entities

People

  • Shlomo Havlin

Organizations

  • Army Contracting Command
  • Bar-Ilan University
  • United States Army

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Educational Psychology
  • Theoretical Analysis.