IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i17p2902-d1744871.html

Hybrid Entropy-Based Metrics for k-Hop Environment Analysis in Complex Networks

Author

Listed:
  • Csaba Biró

    (Faculty of Informatics, Eszterházy Károly Catholic University, 3300 Eger, Hungary
    Faculty of Informatics, Eötvös Loránd University, 1117 Budapest, Hungary)

Abstract

Two hybrid, entropy-guided node metrics are proposed for the k -hop environment: Entropy-Weighted Redundancy (EWR) and Normalized Entropy Density (NED). The central idea is to couple local Shannon entropy with neighborhood density/redundancy so that structural heterogeneity around a vertex is captured even when classical indices (e.g., degree or clustering) are similar. The metrics are formally defined and shown to be bounded, isomorphism-invariant, and stable under small edge edits. Their behavior is assessed on representative topologies (Erdős–Rényi, Barabási–Albert, Watts–Strogatz, random geometric graphs, and the Zephyr quantum architecture). Across these settings, EWR and NED display predominantly negative correlation with degree and provide information largely orthogonal to standard centralities; vertices with identical degree can differ by factors of two to three in the proposed scores, revealing bridges and heterogeneous regions. These properties indicate utility for vulnerability assessment, topology-aware optimization, and layout heuristics in engineered and quantum networks.

Suggested Citation

  • Csaba Biró, 2025. "Hybrid Entropy-Based Metrics for k-Hop Environment Analysis in Complex Networks," Mathematics, MDPI, vol. 13(17), pages 1-27, September.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:17:p:2902-:d:1744871
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/17/2902/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/13/17/2902/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiao, Yang-Hua & Wu, Wen-Tao & Wang, Hui & Xiong, Momiao & Wang, Wei, 2008. "Symmetry-based structure entropy of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2611-2619.
    2. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    3. Jiang, Jiu-Lei & Fang, Hui & Li, Sheng-Qing & Li, Wei-Min, 2022. "Identifying important nodes for temporal networks based on the ASAM model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    4. Jacob Biamonte & Peter Wittek & Nicola Pancotti & Patrick Rebentrost & Nathan Wiebe & Seth Lloyd, 2017. "Quantum machine learning," Nature, Nature, vol. 549(7671), pages 195-202, September.
    5. Passerini, Filippo & Severini, Simone, 2008. "The von Neumann entropy of networks," MPRA Paper 12538, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huan Wang & Chuang Ma & Han-Shuang Chen & Ying-Cheng Lai & Hai-Feng Zhang, 2022. "Full reconstruction of simplicial complexes from binary contagion and Ising data," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Abraham Itzhak Weinberg, 2025. "Hybrid Quantum-Classical Ensemble Learning for S\&P 500 Directional Prediction," Papers 2512.15738, arXiv.org.
    3. Vinayak, & Raghuvanshi, Adarsh & kshitij, Avinash, 2023. "Signatures of capacity development through research collaborations in artificial intelligence and machine learning," Journal of Informetrics, Elsevier, vol. 17(1).
    4. Supriya Tiwari & Pallavi Basu, 2024. "Quasi-randomization tests for network interference: a random graph approach," Papers 2403.16673, arXiv.org, revised Jun 2026.
    5. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    6. Nitsova, Silviya, 2025. "Oligarchic Networks of Influence and Legislatures in Developing Democracies: Evidence from Ukraine," OSF Preprints k27ez_v1, Center for Open Science.
    7. repec:plo:pone00:0082578 is not listed on IDEAS
    8. Wu, Jiang & Ou, Guiyan & Liu, Xiaohui & Dong, Ke, 2022. "How does academic education background affect top researchers’ performance? Evidence from the field of artificial intelligence," Journal of Informetrics, Elsevier, vol. 16(2).
    9. Samrachana Adhikari & Beau Dabbs, 2018. "Social Network Analysis in R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 225-253, April.
    10. Wang, Xiaojie & Slamu, Wushour & Guo, Wenqiang & Wang, Sixiu & Ren, Yan, 2022. "A novel semi local measure of identifying influential nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    11. Lin, Dan & Wu, Jiajing & Xuan, Qi & Tse, Chi K., 2022. "Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    12. Yang, Ping & Lin, Yiping, 2026. "Critical curves and stability region in a complex network with delayed feedback control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 241(PA), pages 548-561.
    13. Zheng, Wei & Wei, Sheng, 2024. "A ‘node-place-network-city’ framework to examine HSR station area development dynamics: Station typologies and development strategies," Journal of Transport Geography, Elsevier, vol. 120(C).
    14. Ferreira, D.S.R. & Ribeiro, J. & Oliveira, P.S.L. & Pimenta, A.R. & Freitas, R.P. & Dutra, R.S. & Papa, A.R.R. & Mendes, J.F.F., 2022. "Spatiotemporal analysis of earthquake occurrence in synthetic and worldwide data," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    15. Mario V. Tomasello & Mauro Napoletano & Antonios Garas & Frank Schweitzer, 2017. "The rise and fall of R&D networks," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(4), pages 617-646.
    16. Qinghu Liao & Wenwen Dong & Boxin Zhao, 2023. "A New Strategy to Solve “the Tragedy of the Commons” in Sustainable Grassland Ecological Compensation: Experience from Inner Mongolia, China," Sustainability, MDPI, vol. 15(12), pages 1-24, June.
    17. Xinyu Huang & Dongming Chen & Dongqi Wang & Tao Ren, 2020. "MINE: Identifying Top- k Vital Nodes in Complex Networks via Maximum Influential Neighbors Expansion," Mathematics, MDPI, vol. 8(9), pages 1-25, August.
    18. Xinbiao Wang & Yuxuan Du & Zhuozhuo Tu & Yong Luo & Xiao Yuan & Dacheng Tao, 2024. "Transition role of entangled data in quantum machine learning," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    19. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    20. Jianhong Chen & Hongcai Ma & Shan Yang, 2023. "SEIOR Rumor Propagation Model Considering Hesitating Mechanism and Different Rumor-Refuting Ways in Complex Networks," Mathematics, MDPI, vol. 11(2), pages 1-22, January.
    21. Pawanesh Pawanesh & Charu Sharma & Niteesh Sahni, 2025. "Analyzing Communicability and Connectivity in the Indian Stock Market During Crises," Papers 2502.08242, arXiv.org, revised Sep 2025.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:13:y:2025:i:17:p:2902-:d:1744871. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.