Influence of Countries in the Global Arms Transfers Network: 1950–2018

  • Sergey ShvydunEmail author
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 882)


Using the SIPRI Arms Transfers Database covering all trade in military equipment over the period 1950–2018, we examine the relationship between countries from a novel empirical perspective. We consider the arms transfers network as a multiplex network where each layer corresponds to a particular armament category. First, we analyze how different layers overlap and elucidate main ties between countries. Second, we consider different patterns of trade in order to identify countries specializing on particular armament categories and analyze how they change their export structure in dynamic. We also examine how countries influence each other at different layers of multiplex network. Finally, we analyze the influence of countries in the whole network.


Arms transfers Influence Multiplex network Dynamic 



The article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project ‘5–100’. The influence analysis of countries (Sect. 3) was funded by the Russian Science Foundation under grant № 17-18-01651.


  1. 1.
    Sislin, J.: Arms as influence: the determinants of successful influence. J. Confl. Resolut. 38(4), 665–689 (1994)CrossRefGoogle Scholar
  2. 2.
    Craft, C., Smaldone, J.: The arms trade and the incidence of political violence in sub-saharan Africa, 1967-97. J. Peace Res. 39(6), 693–710 (2002)CrossRefGoogle Scholar
  3. 3.
    Kinsella, D.: Changing structure of the arms trade: a social network analysis. Presented at the Annual Meeting of the American Political Science Association. Philadelphia, PA (2003)Google Scholar
  4. 4.
    Akerman, A., Seim, A.L.: The global arms trade network 1950–2007. J. Comp. Econ. 42(3), 535–551 (2014)CrossRefGoogle Scholar
  5. 5.
    Thurner, P.W., Schmid, C.S., Cranmer, S.J., Kauermann, G.: Network interdependencies and the evolution of the international arms trade. J. Confl. Resolut. 63(7), 1736–1764 (2019)CrossRefGoogle Scholar
  6. 6.
    Kinsella, D.: Power transition theory and the global arms trade: exploring constructs from social network analysis. Political Science Faculty Publications and Presentations (2013)Google Scholar
  7. 7.
    SIPRI:. The SIPRI Arms transfers database (2019). Accessed 1 July 2019Google Scholar
  8. 8.
    Simmel, V., Holtom, P., Bromley, M.: Measuring international arms transfers. Stockholm International Peace Research Institute (SIPRI) (2012)Google Scholar
  9. 9.
    Freeman, L.C.: Centrality in social networks: conceptual clarification. Soc. Netw. 1, 215–239 (1979)CrossRefGoogle Scholar
  10. 10.
    Bonacich, P., Lloyd, P.: Eigenvector-like measures of centrality for asymmetric relations. Soc. Netw. 23, 191–201 (2001)CrossRefGoogle Scholar
  11. 11.
    Katz, L.: A new status index derived from sociometric index. Psychometrika 18, 39–43 (1953)CrossRefGoogle Scholar
  12. 12.
    Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. J. ACM 46(5), 604–632 (1999)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Freeman, L.C.: A set of measures of centrality based upon betweenness. Sociometry 40, 35–41 (1977)CrossRefGoogle Scholar
  14. 14.
    Rochat, Y.: Closeness centrality extended to unconnected graphs: the harmonic centrality index. ASNA (2009)Google Scholar
  15. 15.
    Aleskerov, F., Meshcheryakova, N, Shvydun, S.: Centrality measures in networks based on nodes attributes, long-range interactions and group influence. arXiv preprint arXiv:1610.05892
  16. 16.
    Aleskerov, F.T., Meshcheryakova, N.G., Shvydun, S.V.: Power in network structures. In: Kalyagin, V.A., Nikolaev, A.I., Pardalos, P.M., Prokopyev, O. (eds.) Models, Algorithms, and Technologies for Network Analysis. Springer Proceedings in Mathematics & Statistics, vol. 197, pp. 79–85. Springer (2017)Google Scholar
  17. 17.
    Wheelock, T.: Arms for Israel: the limit of leverage. Int. Secur. 3(Fall), 123–137 (1978)CrossRefGoogle Scholar
  18. 18.
    Cozzo, E., de Arruda, G.F., Rodrigues, F.A., Moreno, Y.: Multilayer networks: metrics and spectral properties. In: Garas, A. (eds.) Interconnected Networks. Understanding Complex Systems. Springer, Cham (2016)Google Scholar
  19. 19.
    Solé-Ribalta, A., De Domenico, M., Kouvaris, N.E., Díaz-Guilera, A., Gómez, S., Arenas, A.: Spectral properties of the Laplacian of multiplex networks. Phys. Rev. E 88, 032807 (2013)CrossRefGoogle Scholar
  20. 20.
    Shvydun, S.: Influence assessment in multiplex networks using social choice rules. Procedia Comput. Sci. 139, 182–189 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.National Research University Higher School of EconomicsMoscowRussia
  2. 2.V.A. Trapeznikov Institute of Control Sciences of Russian Academy of ScienceMoscowRussia

Personalised recommendations