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Assortative mixing in weighted directed networks

Author

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  • Pigorsch, U.
  • Sabek, M.

Abstract

We analyse assortative mixing, the tendency of vertices to bond with others based on similarities (usually excess vertex degree), in weighted networks, both directed and undirected. We propose a generalisation of the concept of assortativity by introducing our generalised assortativity coefficient. We also provide procedures that allow for both precisely assessing and interpreting the assortativity of weighted networks as well as its statistical significance. Finally, we demonstrate the usefulness of our proposed generalised assortativity coefficient by in-depth analysing the assortativity structure of several weighted real-world networks.

Suggested Citation

  • Pigorsch, U. & Sabek, M., 2022. "Assortative mixing in weighted directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    • Handle: RePEc:eee:phsmap:v:604:y:2022:i:c:s0378437122005519
    DOI: 10.1016/j.physa.2022.127850
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    References listed on IDEAS

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    4. Chang, Hui & Su, Bei-Bei & Zhou, Yue-Ping & He, Da-Ren, 2007. "Assortativity and act degree distribution of some collaboration networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 687-702.
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    Cited by:

    1. Sabek, M. & Pigorsch, U., 2023. "Local assortativity in weighted and directed complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    2. Ricca, Federica & Scozzari, Andrea, 2024. "Portfolio optimization through a network approach: Network assortative mixing and portfolio diversification," European Journal of Operational Research, Elsevier, vol. 312(2), pages 700-717.

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