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Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter

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  • Matthew C Benigni
  • Kenneth Joseph
  • Kathleen M Carley

Abstract

The Islamic State of Iraq and ash-Sham (ISIS) continues to use social media as an essential element of its campaign to motivate support. On Twitter, ISIS’ unique ability to leverage unaffiliated sympathizers that simply retweet propaganda has been identified as a primary mechanism in their success in motivating both recruitment and “lone wolf” attacks. The present work explores a large community of Twitter users whose activity supports ISIS propaganda diffusion in varying degrees. Within this ISIS supporting community, we observe a diverse range of actor types, including fighters, propagandists, recruiters, religious scholars, and unaffiliated sympathizers. The interaction between these users offers unique insight into the people and narratives critical to ISIS’ sustainment. In their entirety, we refer to this diverse set of users as an online extremist community or OEC. We present Iterative Vertex Clustering and Classification (IVCC), a scalable analytic approach for OEC detection in annotated heterogeneous networks, and provide an illustrative case study of an online community of over 22,000 Twitter users whose online behavior directly advocates support for ISIS or contibutes to the group’s propaganda dissemination through retweets.

Suggested Citation

  • Matthew C Benigni & Kenneth Joseph & Kathleen M Carley, 2017. "Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-23, December.
    • Handle: RePEc:plo:pone00:0181405
    DOI: 10.1371/journal.pone.0181405
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    Cited by:

    1. Moradi, Mehdi & Parsa, Saeed, 2019. "An evolutionary method for community detection using a novel local search strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 457-475.
    2. Matthew Benigni & Kenneth Joseph & Kathleen M. Carley, 2018. "Mining online communities to inform strategic messaging: practical methods to identify community-level insights," Computational and Mathematical Organization Theory, Springer, vol. 24(2), pages 224-242, June.
    3. Kathleen M. Carley, 2020. "Social cybersecurity: an emerging science," Computational and Mathematical Organization Theory, Springer, vol. 26(4), pages 365-381, December.
    4. Jose N. Paredes & Gerardo I. Simari & Maria Vanina Martinez & Marcelo A. Falappa, 2021. "NetDER: An Architecture for Reasoning About Malicious Behavior," Information Systems Frontiers, Springer, vol. 23(1), pages 185-201, February.
    5. Ozan Candogan & Nicole Immorlica & Bar Light & Jerry Anunrojwong, 2022. "Social Learning under Platform Influence: Consensus and Persistent Disagreement," Papers 2202.12453, arXiv.org, revised Oct 2023.
    6. Rahma Sugihartati & Bagong Suyanto & Mun’im Sirry, 2020. "The Shift from Consumers to Prosumers: Susceptibility of Young Adults to Radicalization," Social Sciences, MDPI, vol. 9(4), pages 1-15, April.

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