Advertisement

Dynamic Patterns of Terrorist Networks: Efficiency and Security in the Evolution of Eleven Islamic Extremist Attack Networks

  • Cassie McMillanEmail author
  • Diane Felmlee
  • Dave Braines
Original Paper

Abstract

Objectives

The current research examines how the efficiency/security tradeoff shapes the evolution of dynamic terrorist networks by focusing on the structural properties of these collectives. Some scholars argue that terrorist groups develop as chain-like, decentralized structures, while others maintain that terrorist networks form patterns of redundant ties and organize around a few highly connected individuals, or central hubs. We investigate these structural properties and consider whether patterns vary at different phases of a terrorist network’s formation.

Methods

Using a variety of descriptive network measures and Separable Temporal Exponential Random Graph Models, we consider patterns of tie formation across eleven multi-wave terrorism networks from the John Jay & ARTIS Transnational Terrorism database. This dataset includes networks from prominent attacks and bombings that occurred in the last 3 decades (e.g., the 2002 Bali Bombings), where nodes represent individual terrorists and ties represent social relationships.

Results

We find that terrorist groups navigate the efficiency/security tradeoff by developing increasingly well-connected networks as they prepare for a violent incident. Our results also show that highly central nodes acquire even more ties in the years directly preceding an attack, signifying that the evolution of terrorist networks tends to be structured around a few key actors.

Conclusions

Our findings have the potential to inform counterterrorism efforts by suggesting which actors in the network make the most influential targets for law enforcement. We discuss how these strategies should vary as extremist networks evolve over time.

Keywords

Terrorist networks Dynamic networks Transitivity Central hubs Efficiency Security 

Notes

Acknowledgements

This research was sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence under Agreement Number W911NF-16-3-0001. The views and 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 U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon. This work was also supported by Pennsylvania State University and the National Science Foundation under an IGERT award # DGE-1144860, Big Data Social Science.

References

  1. Albert R, Jeong H, Barabási AL (2000) Error and attack tolerance of complex networks. Nature 406:378–382Google Scholar
  2. Armal LAN, Scala A, Barthelemy M, Stanley HE (2000) Classes of small-world networks. Proc Natl Acad Sci 97(21):11149–11152Google Scholar
  3. Asal V, Rethemeyer K (2006) Researching terrorist networks. J Secur Educ 1(4):65–74Google Scholar
  4. Baker WE, Faulkner RR (1993) The social organization of conspiracy: illegal networks in the heavy electrical equipment industry. Am Sociol Rev 58(6):837–860Google Scholar
  5. Bakker RM, Raab J, Milward HW (2011) A preliminary theory of dark network resilience. J Policy Anal Manag 31(1):33–62Google Scholar
  6. Barabási AL, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512Google Scholar
  7. Blau PM (1968) The hierarchy of authority in organizations. Am J Sociol 73(4):453–467Google Scholar
  8. Block P (2015) Reciprocity, transitivity, and the mysterious three-cycle. Soc Netw 40:163–173Google Scholar
  9. Block P, Koskinen J, Holloway J, Steglich C, Stadtfeld C (2018) Change we can believe in: comparing longitudinal network models on consistency, interpretability and predictive power. Soc Netw 52:180–191Google Scholar
  10. Bright D, Koskinen J, Malm A (2018) Illicit network dynamics: the formation and evolution of a drug trafficking network. J Quant Criminol.  https://doi.org/10.1007/s10940-018-9379-8 CrossRefGoogle Scholar
  11. Carley KM (2006) Destabilization of covert networks. Comput Math Organ Theory 12(1):51–66Google Scholar
  12. Crossley N, Edwards G, Harries E, Stevenson R (2012) Covert social movement networks and the secrecy-efficiency trade off: the case of the UK suffragettes (1906–1914). Soc Networks 34:634–644Google Scholar
  13. Cunningham D, Everton S, Murphy P (2016) Understanding dark networks: a strategic framework for the use of social network analysis. Rowman & Littlefield, LandhamGoogle Scholar
  14. Desmarais BA, Cranmer SJ (2012) Micro-level interpretation of exponential random graph models with application to estuary networks. Policy Stud J 40(3):402–434Google Scholar
  15. Duxbury SW, Haynie DL (2019) Criminal network security: an agent-based approach to evaluating network resilience. Criminology 57(2):314–342Google Scholar
  16. Enders W, Su X (2007) Rational terrorists and optimal network structure. J Confl Resolut 51(1):33–57Google Scholar
  17. Erickson BH (1981) Secret societies and social structure. Soc Forces 60(1):188–210Google Scholar
  18. Everton SF (2012) Disrupting dark networks. Cambridge University Press, New YorkGoogle Scholar
  19. Everton SF (2016) Social networks and religious violence. Rev Relig Res 58(2):191–217Google Scholar
  20. Felmlee D, Faris R (2016) Toxic ties: a network of friendship, dating, and cyber victimization. Soc Psychol Q 79:243–262Google Scholar
  21. Felmlee D, McMillan C, Inara Rodis P, Osgood DW (2018) Falling behind: lingering costs of the high school transition for youth friendships and grades. Sociol Educ 91(2):159–182Google Scholar
  22. Gartner SS, Felmlee D, Yarlagadda R, Verma D (2019) Understanding patterns of terrorism in India using AI machine learning: 2007–2017. In: Fifteenth international conference on technology, knowledge & society, BarcelonaGoogle Scholar
  23. Gerdes LM (2015) Dark dimensions: clarifying relationships among clandestine actors. In: Gerdes LM (ed) Illuminating dark networks: the study of clandestine groups and organizations. Cambridge University Press, New York, pp 19–38Google Scholar
  24. Gill P, Lee J, Rethemeyer KR, Horgan J, Asal V (2014) Lethal connections: the determinants of networks connections in the Provisional Irish Republican Army, 1970–1998. Int Interact 40(1):52–78Google Scholar
  25. Granovetter MS (1973) The strength of weak ties. Am J Sociol 78(6):1360–1380Google Scholar
  26. Helfstein S, Wright D (2011) Covert or convenient? Evolution of terror attack networks. J Confl Resolut 55(5):785–813Google Scholar
  27. Horowitz MC, Potter PBK (2014) Allying to kill: terrorist intergroup cooperation and the consequences for lethality. J Confl Resolut 58(2):199–225Google Scholar
  28. Hunter DR (2007) Curved exponential family models for social networks. Soc Netw 29:216–230Google Scholar
  29. Hunter DR, Handcock MS, Butts CT, Goodreau SM, Morris M (2008) ergm: a package to fit, simulate and diagnose exponential-family models for networks. J Stat Softw 24(3):1–29Google Scholar
  30. John Jay & ARTIS Transnational Terrorism (JJATT) database (2009) http://doitapps.jjay.cuny.edu/jjatt/index.php. Accessed 4 May 2018
  31. Knoke D (2013) ‘It takes a network:’ the rise and fall of social network analysis in U.S. army counterinsurgency doctrine. Connections 33(1):1–10Google Scholar
  32. Krebs VE (2002) Mapping networks of terrorist cells. Connections 24(3):23–52Google Scholar
  33. Krivitsky PN, Goodreau SM (2017) STERGM—separable temporal ERGMs for modeling discrete relational dynamics with statnetGoogle Scholar
  34. Lantz B, Hutchison R (2015) Co-offender ties and the criminal career: the relationship between co-offender group structure and the individual offender. J Res Crime Delinq 52(5):658–690Google Scholar
  35. Lubbers MJ, Snijders TAB (2007) A comparison of various approaches to the exponential random graph model: a reanalysis of 102 student networks in school classes. Soc Netw 29(4):489–507Google Scholar
  36. Magouirk J, Atran S, Sageman M (2008) Connecting terrorist networks. Stud Confl Terror 31(1):1–16Google Scholar
  37. Maoz Z, Terris LG, Kuperman RD, Talmund I (2007) What is the enemy of my enemy? Causes and consequences of imbalanced international relations, 1816–2001. J Polit 69(1):100–115Google Scholar
  38. Matthew R, Shambaugh G (2005) The limits of terrorism: a network perspective. Int Stud Rev 7(4):617–627Google Scholar
  39. McAllister B (2004) Al Qaeda and the innovative firm: demythologizing the network. Stud Confl Terror 27(4):297–319Google Scholar
  40. McFarland DA, Moody J, Diehl D, Smith JA, Thomas RJ (2014) Network ecology and adolescent social structure. Am Sociol Rev 79(6):1088–1121Google Scholar
  41. McMillan C (2019) Tied together: adolescent friendship networks, immigrant status, and health outcomes. Demography 56(3):1075–1103Google Scholar
  42. McMillan C, Felmlee D, Osgood DW (2018) Peer influence, friend selection, and gender: how network processes shape adolescent smoking, drinking, and delinquency. Soc Netw 55:86–96Google Scholar
  43. Milward HB, Raab J (2006) Dark networks as organizational problems: elements of a theory. Int Public Manag J 9(3):333–360Google Scholar
  44. Morselli C, Giguère C, Petit K (2007) The efficiency/security trade-off in criminal networks. Soc Netw 29:143–153Google Scholar
  45. Newcomb TM (1961) The acquaintance process. Holt, Rinehart & Winston, New YorkGoogle Scholar
  46. Newman MEJ (2001) Clustering and preferential attachment in growing networks. Phys Rev E 64:1–4Google Scholar
  47. Osgood DW, Ragan DT, Wallace L, Gest SD, Feinberg ME, Moody J (2013) Peers and the emergence of alcohol use: influence and selection processes in adolescent friendship networks. J Res Adolesc 23(3):500–512Google Scholar
  48. Papachristos AV (2009) Murder by structure: dominance relations and the social structure of gang homicide. Am J Sociol 115(1):74–128Google Scholar
  49. Pedahzur A, Perliger A (2006) The changing nature of suicide attacks. Soc Forces 84(4):1987–2008Google Scholar
  50. Perliger A (2018) Terrorism networks. In: Victor JN, Montgomery AH, Lubell M (eds) The oxford handbook of political networks. Oxford University Press, New York, pp 653–668Google Scholar
  51. Pirolli P, Card S (2005) The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In: Proceedings of international conference on intelligence analysis, p 4Google Scholar
  52. Price DD (1976) A theory of bibliometric and other cumulative advantage processes. J Am Soc Inf Sci 27(5):292–306Google Scholar
  53. Robins G, Pattison P, Kalish Y, Lusher D (2007) An introduction to exponential random graph (p*) models for social networks. Soc Netw 29(2):173–191Google Scholar
  54. Rodríguez JA (2005) The March 11th terrorist network: in its weakness lies its strength. EPP-LEA working papersGoogle Scholar
  55. Sageman M (2004) Understanding terror networks. University of Pennsylvania Press, PhiladelphiaGoogle Scholar
  56. Sageman M (2008) The next generation of terror. Foreign Policy 165:37–42Google Scholar
  57. Schaefer DR, Marcum CS (2018) Modeling network dynamics. SocArXiv  https://doi.org/10.17605/osf.io/6rm9q
  58. Schaefer DR, Simpkins SD, Vest AE, Price CD (2011) The contributions of extracurricular activities to adolescent friendships: new insights through social network analysis. Dev Psychol 47(4):1141–1152Google Scholar
  59. Simmel G (1906) The sociology of secrecy and of secret societies. Am J Sociol 11(4):441–498Google Scholar
  60. Snijders TAB, Baerveldt C (2003) A multilevel network study of the effects of delinquent behavior on friendship evolution. J Math Sociol 27(2–3):123–151Google Scholar
  61. Snijders TAB, Pattison PA, Robins GL, Handcock MS (2006) New specifications for exponential random graph models. Sociol Methodol 36(1):99–153Google Scholar
  62. Snijders TAB, van de Bunt GG, Steglich CEG (2010) Introduction to stochastic actor-based models for network dynamics. Soc Netw 32(1):44–60Google Scholar
  63. Steglich C, Snijders TAB, Pearson M (2010) Dynamic networks and behavior: separating selection from influence. Sociol Methodol 40:329–393Google Scholar
  64. Stevenson R, Crossley N (2014) Change in covert movement networks: the ‘inner circle’ of the Provisional Irish Republican Army. Soc Mov Stud 13(1):70–91Google Scholar
  65. Stohl C, Stohl M (2007) Networks of terror: theoretical assumptions and pragmatic consequences. Commun Theor 17(2):93–124Google Scholar
  66. Ünal MC (2019) Do terrorists make a difference in criminal networks? An empirical analysis on illicit drug and narco-terror networks in the prioritization between security and efficiency. Soc Netw 57:1–17Google Scholar
  67. Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, CambridgeGoogle Scholar
  68. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(4):440–442Google Scholar
  69. Weerman FM (2011) Delinquent peers in context: a longitudinal network analysis of selection and influence effects. Criminology 49(1):253–286Google Scholar
  70. White G, Porter MD, Mazerolle L (2013) Terrorism risk, resilience and volatility: a comparison of terrorism patterns in three southeast Asian countries. J Quant Criminol 29(2):295–320Google Scholar
  71. Widmer ED (1999) Family contexts as cognitive networks: a structural approach of family relationships. Pers Relatsh 6(4):487–503Google Scholar
  72. Wood G (2017) The structure and vulnerability of a drug trafficking collaboration network. Soc Netw 48:1–9Google Scholar
  73. Yarlagadda R, Felmlee D, Verma D, Gartner S (2018) Implicit terrorist networks: a two-mode social network analysis of terrorism in India. SBP-BRiMS 2018. LNCS 10899:1–8Google Scholar
  74. Zech ST, Gabbay M (2016) Social network analysis in the study of terrorism and insurgency: from organization to politics. Int Stud Rev 18:214–243Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Sociology and CriminologyPennsylvania State UniversityUniversity ParkUSA
  2. 2.IBM ResearchWinchesterUK

Personalised recommendations