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Using Behavior and Text Analysis to Detect Propagandists and Misinformers on Twitter

  • Michael OrlovEmail author
  • Marina LitvakEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 898)

Abstract

There are organized groups that disseminate similar messages in online forums and social media; they respond to real-time events or as persistent policy, and operate with state-level or organizational funding. Identifying these groups is of vital importance for preventing distribution of sponsored propaganda and misinformation. This paper presents an unsupervised approach using behavioral and text analysis of users and messages to identify groups of users who abuse the Twitter micro-blogging service to disseminate propaganda and misinformation. Groups of users who frequently post strikingly similar content at different times are identified through repeated clustering and frequent itemset mining, with the lack of credibility of their content validated through human assessment. This paper introduces a case study into automatic identification of propagandists and misinformers in social media.

Keywords

Propaganda Misinformation Social networks 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.NoExecBeer ShevaIsrael
  2. 2.Shamoon College of EngineeringBeer ShevaIsrael

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