From Tweets to Intelligence: Understanding the Islamic Jihad Supporting Community on Twitter

  • Matthew BenigniEmail author
  • Kathleen M. Carley
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9708)


ISIS’ ability to build and maintain a large online community that disseminates propaganda and garners support continues to give their message global reach. Although these communities contain trained media cadre, recent literature suggests that large numbers of “unaffiliated sympathizers” who simply retweet or repost propaganda explain ISIS’ unprecedented online success [1, 2]. Tailored methodologies to detect and study these online threat-group-supporting communities (OTGSC) could help provide the understanding needed to craft effective counter-narratives however continued development of these methods will require collaboration between data scientists and regional experts. We illustrate the potential of this partnership using two ongoing projects at the Center for Computational Analysis of Social and Organizational Systems (CASOS) at Carnegie Mellon University. First we present the CASOS Jihadist Twitter Community (CJTC), an online community of over 15,000 Twitter users that support one or more of the Islamic extremist groups engaged in the ongoing conflicts in Northern Iraq and Syria. We briefly discuss the methods used to detect and monitor these communities and highlight forms of information that can be extracted from them. We then present an active social botnet that attempts to elevate the social influence of users supportive to Jabhat al-Nusra’s agenda. In each case we highlight the ability of these methods to incorporate regional expertise for better performance and recommend future research.


Threat network detection Community detection Social media intelligence Online social networks Social bots ISIS Radicalization 



This work was supported in part by the Office of Naval Research (ONR) through a MINERVA N000141310835 on State Stability. Additional support for this project was provided by the center for Computational Analysis of Social and Organizational Systems (CASOS) at CMU. The views ond conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Office of Naval Research or the U.S. Government.


  1. 1.
    Yannick Veilleux-Lepage. Paradigmatic Shifts in Jihadism in Cyberspace: The Emerging Role of Unaffiliated Sympathizers in the Islamic State's Social Media Strategy (2015)Google Scholar
  2. 2.
    Berger, JM.: Tailored Online Interventions: The Islamic States RecruitmentStrategy. Combating Terrorism Center SentinelGoogle Scholar
  3. 3.
    Dozier, K.: Anti-ISIS-Propaganda Czars Ninja War Plan: We Were Never Here, March 2016Google Scholar
  4. 4.
    Isaac, M.: Twitter Steps Up Efforts to Thwart Terrorists’ Tweets. The New York Times (2016).
  5. 5.
    Benigni, M., Joseph, K., Carley, K.: Threat Group Detection in Social Media: Uncovering the ISIS Supporting Network on Twitter. Submitted to Plos OneGoogle Scholar
  6. 6.
    Krebs, V.: Uncloaking terrorist networks. First Monday 7(4), 215–235 (2002)CrossRefGoogle Scholar
  7. 7.
    Carley, K.M.: A Dynamic Network Approach to the Assessment of Terrorist Groups and the Impact of Alternative Courses of Action. Technical report, October 2006Google Scholar
  8. 8.
    Tang, L., Liu, H.: Leveraging social media networks for classification. Data Min. Knowl. Discov. 23(3), 447–478 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Binkiewicz, N., Vogelstein, J.T., Rohe, K.: Clustering, Covariate Assisted Spectral (2014). arXiv preprint arXiv: 1411.2158
  10. 10.
    Carter, J.A., Maher, S., Neumann, P.R.: #Greenbirds Measuring Importance and Influence in Syrian Foreign Fighter Networks. International Centre for the Study of Radicalization Report, April 2014Google Scholar
  11. 11.
    Syria ceasefire ends, fighting resumes. Reuters, August 2015Google Scholar
  12. 12.
    Abokhodair, N., Yoo, D., McDonald, D.W.: Dissecting a Social Botnet: Growth, Content and Influence in Twitter, pp. 839–851. ACM Press (2015)Google Scholar
  13. 13.
    Berger, J.M.: How ISIS Games Twitter. The Atlantic, June 2014Google Scholar
  14. 14.
    Ferrara, E., Varol, O., Davis, C., Menczer, F., Flammini, A.: The rise of social bots (2014). arXiv preprint arXiv: 1407.5225
  15. 15.
    Forelle, M., Howard, P., Monroy-Hernndez, A., Savage, S.: Political Bots the Manipulation of Public Opinion in Venezuela. arXiv: 1507.07109 [physics]. arxiv: 1507.07109, July 2015
  16. 16.
    Subrahmanian, V.S., Azaria, A., Durst, S., Kagan, V., Galstyan, A., Lerman, K., Zhu, L., Ferrara, E., Flammini, A., Menczer, F., Waltzman, R., Stevens, A., Dekhtyar, A., Gao, S., Hogg, T., Kooti, F., Liu, Y., Varol, O., Shiralkar, P., Vydiswaran, V., Mei, Q., Huang, T.: The DARPATwitter Bot Challenge. arXiv: 1601.05140 [physics]. arxiv: 1601.05140, January 2016
  17. 17.
    Ansar al-Sharia Tunisias and Long Game. Dawa, hisba, and jihad (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Center for Computational Analysis of Social and Organizational Systems (CASOS), Institute for Software ResearchCarnegie Mellon UniversityPittsburgUSA

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