IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v129y2024i11d10.1007_s11192-024-05170-5.html
   My bibliography  Save this article

H-core decomposition for directed networks and its application

Author

Listed:
  • Xiaoyu Chen

    (Shaanxi Normal University
    Zhejiang Normal University)

  • Yang Liu

    (Zhejiang Normal University
    Yili Normal University)

  • Zhenxin Cao

    (Zhejiang Normal University)

  • Xiaopeng Li

    (Northwest A&F University)

  • Jinde Cao

    (Southeast University
    Ahlia University)

Abstract

In this paper, we introduce a directed weighted h-index and a bi-directional h-core decomposition for directed networks, aimed at better identifying important nodes and dense subgraphs. This directed weighted h-index combines the edges’ direction and weight in a directed network, and it can effectively measure the centrality of nodes. To obtain the h-core, we design an iterative algorithm, and we develop a bi-directional h-core decomposition method for partitioning the nodes in a network. As an application, we apply the directed weighted h-index and algorithm to the CEL neural network, USAir network and Social network to identify dense subgraphs and important nodes. Comparative analysis with existing h-type indices demonstrates that our proposed directed weighted h-index is a superior measure of centrality in terms of its ability to identify important nodes and dense subgraphs more accurately.

Suggested Citation

  • Xiaoyu Chen & Yang Liu & Zhenxin Cao & Xiaopeng Li & Jinde Cao, 2024. "H-core decomposition for directed networks and its application," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 6571-6596, November.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:11:d:10.1007_s11192-024-05170-5
    DOI: 10.1007/s11192-024-05170-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-024-05170-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-024-05170-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhao, Star X. & Rousseau, Ronald & Ye, Fred Y., 2011. "h-Degree as a basic measure in weighted networks," Journal of Informetrics, Elsevier, vol. 5(4), pages 668-677.
    2. Yan, Xiangbin & Zhai, Li & Fan, Weiguo, 2013. "C-index: A weighted network node centrality measure for collaboration competence," Journal of Informetrics, Elsevier, vol. 7(1), pages 223-239.
    3. Zhai, Li & Yan, Xiangbin & Zhang, Guojing, 2018. "Bi-directional h-index: A new measure of node centrality in weighted and directed networks," Journal of Informetrics, Elsevier, vol. 12(1), pages 299-314.
    4. Linyuan Lü & Yi-Cheng Zhang & Chi Ho Yeung & Tao Zhou, 2011. "Leaders in Social Networks, the Delicious Case," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-9, June.
    5. Li Zhai & Xiangbin Yan & Bin Zhu, 2014. "The H l -index: improvement of H-index based on quality of citing papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1021-1031, February.
    6. Zhao, Star X. & Ye, Fred Y., 2012. "Exploring the directed h-degree in directed weighted networks," Journal of Informetrics, Elsevier, vol. 6(4), pages 619-630.
    7. Deise Deolindo Silva & Maria Cláudia Cabrini Grácio, 2021. "Dispersion measures for h-index: a study of the Brazilian researchers in the field of mathematics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 1983-2011, March.
    8. Linyuan Lü & Tao Zhou & Qian-Ming Zhang & H. Eugene Stanley, 2016. "The H-index of a network node and its relation to degree and coreness," Nature Communications, Nature, vol. 7(1), pages 1-7, April.
    9. Prem Kumar Singh, 2022. "t-index: entropy based random document and citation analysis using average h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 637-660, January.
    10. Tianlong Fan & Hao Li & Xiao-Long Ren & Shuqi Xu & Youzhao Gou & Linyuan Lü, 2021. "The rise and fall of countries on world trade web: A network perspective," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 32(08), pages 1-19, August.
    11. Korn, A. & Schubert, A. & Telcs, A., 2009. "Lobby index in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(11), pages 2221-2226.
    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. Zhai, Li & Yan, Xiangbin & Zhang, Guojing, 2018. "Bi-directional h-index: A new measure of node centrality in weighted and directed networks," Journal of Informetrics, Elsevier, vol. 12(1), pages 299-314.
    2. Rousseau, Ronald & Zhao, Star X., 2015. "A general conceptual framework for characterizing the ego in a network," Journal of Informetrics, Elsevier, vol. 9(1), pages 145-149.
    3. Wang, Ruby W. & Wei, Shelia X. & Ye, Fred Y., 2021. "Extracting a core structure from heterogeneous information network using h-subnet and meta-path strength," Journal of Informetrics, Elsevier, vol. 15(3).
    4. Yang, Alex Jie & Wu, Linwei & Zhang, Qi & Wang, Hao & Deng, Sanhong, 2023. "The k-step h-index in citation networks at the paper, author, and institution levels," Journal of Informetrics, Elsevier, vol. 17(4).
    5. Zhai, Li & Yan, Xiangbin & Zhang, Guojing, 2013. "A centrality measure for communication ability in weighted network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6107-6117.
    6. Alireza Abbasi, 2013. "h-Type hybrid centrality measures for weighted networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 633-640, August.
    7. Yan, Xiangbin & Zhai, Li & Fan, Weiguo, 2013. "C-index: A weighted network node centrality measure for collaboration competence," Journal of Informetrics, Elsevier, vol. 7(1), pages 223-239.
    8. András Schubert, 2015. "Rescaling the h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1647-1653, February.
    9. Judit Bar-Ilan & Mark Levene, 2015. "The hw-rank: an h-index variant for ranking web pages," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2247-2253, March.
    10. Wang, Jingjing & Xu, Shuqi & Mariani, Manuel S. & Lü, Linyuan, 2021. "The local structure of citation networks uncovers expert-selected milestone papers," Journal of Informetrics, Elsevier, vol. 15(4).
    11. Lee, Yan-Li & Zhou, Tao, 2017. "Fast asynchronous updating algorithms for k-shell indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 524-531.
    12. Zareie, Ahmad & Sheikhahmadi, Amir, 2019. "EHC: Extended H-index Centrality measure for identification of users’ spreading influence in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 141-155.
    13. Guijie Zhang & Luning Liu & Fangfang Wei, 2019. "Key nodes mining in the inventor–author knowledge diffusion network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 721-735, March.
    14. Li Zhai & Xiangbin Yan & Bin Zhu, 2014. "The H l -index: improvement of H-index based on quality of citing papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1021-1031, February.
    15. Wei, Shelia X. & Tong, Tong & Rousseau, Ronald & Wang, Wanru & Ye, Fred Y., 2022. "Relations among the h-, g-, ψ-, and p-index and offset-ability," Journal of Informetrics, Elsevier, vol. 16(4).
    16. Xu, Shuqi & Mariani, Manuel Sebastian & Lü, Linyuan & Medo, Matúš, 2020. "Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data," Journal of Informetrics, Elsevier, vol. 14(1).
    17. Zhang, Ronda J. & Ye, Fred Y., 2020. "Measuring similarity for clarifying layer difference in multiplex ad hoc duplex information networks," Journal of Informetrics, Elsevier, vol. 14(1).
    18. Wen Zhou & Jiayi Gu & Yifan Jia, 2018. "h-Index-based link prediction methods in citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 381-390, October.
    19. Liu, Qiang & Zhu, Yu-Xiao & Jia, Yan & Deng, Lu & Zhou, Bin & Zhu, Jun-Xing & Zou, Peng, 2018. "Leveraging local h-index to identify and rank influential spreaders in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 379-391.
    20. Zhao, Star X. & Tan, Alice M. & Yu, Shuang & Xu, Xin, 2018. "Analyzing the research funding in physics: The perspective of production and collaboration at institution level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 662-674.

    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:spr:scient:v:129:y:2024:i:11:d:10.1007_s11192-024-05170-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.