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Clustering coefficients as measures of the complex interactions in a directed weighted multilayer network

Paolo Bartesaghi, Gian Paolo Clemente, Rosanna Grassi

arXiv 13 Jun 2022 · Econometrics · publishedPhysica A Statistical Mechanics and its Applications (2022) · 18 citations (OpenAlex)

arXiv:2206.06309 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In this paper, we provide novel definitions of clustering coefficient for weighted and directed multilayer networks. We extend in the multilayer theoretical context the clustering coefficients proposed in the literature for weighted directed monoplex networks. We quantify how deeply a node is involved in a choesive structure focusing on a single node, on a single layer or on the entire system. The coefficients convey several characteristics inherent to the complex topology of the multilayer network. We test their effectiveness applying them to a particularly complex structure such as the international trade network. The trade data integrate different aspects and they can be described by a directed and weighted multilayer network, where each layer represents import and export relationships between countries for a given sector. The proposed coefficients find successful application in describing the interrelations of the trade network, allowing to disentangle the effects of countries and sectors and jointly consider the interactions between them.

Citation extraction

34
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Clemente, G. P., & Grassi, R (2018) Directed clustering in weighted networks: a new perspective self1.00053100%
2Fagiolo, G (2007) Clustering in complex directed networks1.00053100%
3De Domenico, M., Solé-Ribalta, A., Cozzo, E., Kivelä, M., Moreno, Y.… (2013) Mathematical formulation of multilayer networks0.81142100%
4Timmer, M., Dietzenbacher, E., Los, B., Stehrer, R., & de Vries, G. J (2015) An illustrated user guide to the world input–output database: the case of global automotive production0.73732100%
5Bartesaghi, P., Clemente, G. P., & Grassi, R (2022) A tensor-based unified approach for clustering coefficients in financial multiplex networks self0.64422100%
6Kivelä, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y.,… (2014) Multilayer networks0.64422100%
7Cozzo, E., Kivelä, M., De Domenico, M., Solé-Ribalta, A., Arenas, A.… (2015) Structure of triadic relations in multiplex networks0.51121100%
8A. Alves, L. G., Mangioni, G., Rodrigues, F. A., Panzarasa, P., & Mo… (2018) Unfolding the complexity of the global value chain: Strength and entropy in the single-layer, multiplex, and multi-layer interna…0.40511100%
9A. Alves, L. G., Mangioni, G., Cingolani, I., Rodrigues, F. A., Panz… (2019) The nested structural organization of the worldwide trade multi-layer network0.40511100%
10A. Alves, L. G., Mangioni, G., Rodrigues, F. A., Panzarasa, P., & Mo… (2022) The rise and fall of countries in the global value chains0.40511100%

Showing the top 10 of 34 scored citations.