The fake news graph analyzer: An open-source software for characterizing spreaders in large diffusion graphs

Amirhosein Bodaghi, Jonice Oliveira, Jonathan J. H. Zhu

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

In the study of fake news spreading, it is essential to know how different types of spreaders differ in terms of their characteristics, interconnections, and cascading flow. The fake news graph analyzer (FNGA) is an open-source software that provides the required computations for such extended analyses on large graphs. Moreover, FNGA generates data for graph visualizations. Also, FNGA is designed to consider the spreading of both fake and true news simultaneously in the graph, leading to a variety of confrontational patterns. FNGA facilitates future research on fake news and the diffusion of any contagion within a graph of entities.
Original languageEnglish
Pages (from-to)1-3
Number of pages3
JournalSoftware Impacts
Volume10
DOIs
Publication statusPublished (in print/issue) - 26 Nov 2021

Keywords

  • Fake news
  • Social network
  • Spreading process
  • Graph analysis
  • Twitter

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