An Empirical Study on Collective Online Behaviors of Extremist Supporters

  • Jung-jae Kim
  • Yong Liu
  • Wee Yong Lim
  • Vrizlynn L. L. Thing
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10604)

Abstract

Online social media platforms such as Twitter have been found to be misused by extremist groups, including Islamic State of Iraq and Syria (ISIS), who attract and recruit social media users. To prevent their influence from expanding in the online social media platforms, it is required to understand the online behaviors of these extremist group users and their followers, for predicting and identifying potential security threats. We present an empirical study about ISIS followers’ online behaviors on Twitter, proposing to classify their tweets in terms of political and subjectivity polarities. We first develop a supervised classification model for the polarity classification, based on natural language processing and clustering methods. We then develop a statistical analysis of term-polarity correlations, which leads us to successfully observe ISIS followers’ online behaviors, which are in line with the reports of experts.

Keywords

Extremist online behavior Social media analysis Polarity-based classification 

Notes

Acknowledgement

This material is based on research work supported by the Singapore National Research Foundation under NCR Award No. NRF2014NCR-NCR001-034.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jung-jae Kim
    • 1
  • Yong Liu
    • 1
  • Wee Yong Lim
    • 1
  • Vrizlynn L. L. Thing
    • 1
  1. 1.Institute for Infocomm ResearchSingaporeSingapore

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