Graph-Based Semi-Supervised and Supervised Approaches for Detecting Pathogenic Social Media Accounts

Hamidreza Alvari, Elham Shaabani, Paulo Shakarian

Research output: Chapter in Book/Report/Conference proceedingChapter


In this chapter, we adopt the causal inference framework described previously along with graph-based metrics to distinguish PSMs from normal users within a short time of their activities. We propose both supervised and semi-supervised approaches without taking the network information and content into account. Results on the ISIS-A dataset demonstrate the advantage of our proposed frameworks. We show our approach achieves 0.28 improvement in F1 score over existing approaches with the precision of 0.90 and F1 score of 0.63.

Original languageEnglish (US)
Title of host publicationSpringerBriefs in Computer Science
Number of pages13
StatePublished - 2021

Publication series

NameSpringerBriefs in Computer Science
ISSN (Print)2191-5768
ISSN (Electronic)2191-5776

ASJC Scopus subject areas

  • General Computer Science

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