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Triadic motifs and dyadic self-organization in the World Trade Network

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  • Tiziano Squartini
  • Diego Garlaschelli

Abstract

In self-organizing networks, topology and dynamics coevolve in a continuous feedback, without exogenous driving. The World Trade Network (WTN) is one of the few empirically well documented examples of self-organizing networks: its topology strongly depends on the GDP of world countries, which in turn depends on the structure of trade. Therefore, understanding which are the key topological properties of the WTN that deviate from randomness provides direct empirical information about the structural effects of self-organization. Here, using an analytical pattern-detection method that we have recently proposed, we study the occurrence of triadic "motifs" (subgraphs of three vertices) in the WTN between 1950 and 2000. We find that, unlike other properties, motifs are not explained by only the in- and out-degree sequences. By contrast, they are completely explained if also the numbers of reciprocal edges are taken into account. This implies that the self-organization process underlying the evolution of the WTN is almost completely encoded into the dyadic structure, which strongly depends on reciprocity.

Suggested Citation

  • Tiziano Squartini & Diego Garlaschelli, 2012. "Triadic motifs and dyadic self-organization in the World Trade Network," Papers 1201.1215, arXiv.org, revised Jan 2012.
  • Handle: RePEc:arx:papers:1201.1215
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    References listed on IDEAS

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    1. D. Garlaschelli & T. Di Matteo & T. Aste & G. Caldarelli & M. I. Loffredo, 2007. "Interplay between topology and dynamics in the World Trade Web," Papers physics/0701030, arXiv.org.
    2. D. Garlaschelli & T. Di Matteo & T. Aste & G. Caldarelli & M. I. Loffredo, 2007. "Interplay between topology and dynamics in the World Trade Web," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 159-164, May.
    3. D. Garlaschelli & M. I. Loffredo, 2004. "Fitness-dependent topological properties of the World Trade Web," Papers cond-mat/0403051, arXiv.org, revised Oct 2004.
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    Cited by:

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    6. Qian Liu & Huajiao Li & Feng An & Nairong Liu & Qing Guan & Jingjing Jia & Pengli An, 2018. "A Motif-Based Analysis to Reveal Local Implied Information in Cross-Shareholding Networks," Complexity, Hindawi, vol. 2018, pages 1-12, December.
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