IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v12y2018i1p299-314.html
   My bibliography  Save this article

Bi-directional h-index: A new measure of node centrality in weighted and directed networks

Author

Listed:
  • Zhai, Li
  • Yan, Xiangbin
  • Zhang, Guojing

Abstract

This paper builds an index family, named bi-directional h-index, to measure node centrality in weighted directed networks. Bi-directional h-index takes the directed degree centrality as the initial value and iteratively uses more network information to update the node’s importance. We prove the convergence of the iterative process after finite iterations and introduce an asynchronous updating process that provides a decentralized, local method to calculate the bi-directional h-index in large-scale networks and dynamic networks. The theoretical analysis manifests that the bi-directional h-index is feasible and significant for establishing a greater conceptual framework that includes some existing index concepts, such as lobby index, node’s h-index, c-index and iterative c-index. An example using journal citation networks indicates that the bi-directional h-index is different from directed degree centrality, directed node strength, directed h-degree and the HITS algorithm in ranking node importance. It is irreplaceable and can reflect these measures of node’s importance.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:infome:v:12:y:2018:i:1:p:299-314
    DOI: 10.1016/j.joi.2018.01.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157717301591
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2018.01.004?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. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 581-603, December.
    2. 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.
    3. 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.
    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. Ronald Rousseau, 2012. "Comments on “A Hirsch-type index of co-author partnership ability”," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 309-310, April.
    6. 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.
    7. 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.
    8. 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.
    9. Flaviano Morone & Hernán A. Makse, 2015. "Influence maximization in complex networks through optimal percolation," Nature, Nature, vol. 524(7563), pages 65-68, August.
    10. 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.
    11. Gao, Cai & Wei, Daijun & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2013. "A modified evidential methodology of identifying influential nodes in weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5490-5500.
    12. András Schubert, 2012. "A Hirsch-type index of co-author partnership ability," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 303-308, April.
    13. Chen, Duanbing & Lü, Linyuan & Shang, Ming-Sheng & Zhang, Yi-Cheng & Zhou, Tao, 2012. "Identifying influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1777-1787.
    14. Chen, P. & Xie, H. & Maslov, S. & Redner, S., 2007. "Finding scientific gems with Google’s PageRank algorithm," Journal of Informetrics, Elsevier, vol. 1(1), pages 8-15.
    15. 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.
    16. Wei, Bo & Liu, Jie & Wei, Daijun & Gao, Cai & Deng, Yong, 2015. "Weighted k-shell decomposition for complex networks based on potential edge weights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 277-283.
    17. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    18. 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.
    19. Leo Egghe, 2010. "Influence of adding or deleting items and sources on the h-index," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(2), pages 370-373, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    2. 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.
    3. 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).

    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. 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.
    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. Wang, Zhixiao & Zhao, Ya & Xi, Jingke & Du, Changjiang, 2016. "Fast ranking influential nodes in complex networks using a k-shell iteration factor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 171-181.
    4. 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).
    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. 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).
    7. Wang, Yan & Li, Haozhan & Zhang, Ling & Zhao, Linlin & Li, Wanlan, 2022. "Identifying influential nodes in social networks: Centripetal centrality and seed exclusion approach," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    8. Namtirtha, Amrita & Dutta, Animesh & Dutta, Biswanath, 2018. "Identifying influential spreaders in complex networks based on kshell hybrid method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 310-324.
    9. Yu, Senbin & Gao, Liang & Xu, Lida & Gao, Zi-You, 2019. "Identifying influential spreaders based on indirect spreading in neighborhood," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 418-425.
    10. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Zareie, Ahmad, 2017. "Identification of influential users by neighbors in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 517-534.
    11. Zhong, Lin-Feng & Shang, Ming-Sheng & Chen, Xiao-Long & Cai, Shi-Ming, 2018. "Identifying the influential nodes via eigen-centrality from the differences and similarities of structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 77-82.
    12. Bao, Zhong-Kui & Ma, Chuang & Xiang, Bing-Bing & Zhang, Hai-Feng, 2017. "Identification of influential nodes in complex networks: Method from spreading probability viewpoint," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 391-397.
    13. 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).
    14. Zhong, Lin-Feng & Liu, Quan-Hui & Wang, Wei & Cai, Shi-Min, 2018. "Comprehensive influence of local and global characteristics on identifying the influential nodes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 78-84.
    15. Wu, Tao & Xian, Xingping & Zhong, Linfeng & Xiong, Xi & Stanley, H. Eugene, 2018. "Power iteration ranking via hybrid diffusion for vital nodes identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 802-815.
    16. 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.
    17. Xie, Zheng & Lv, Yiqin & Song, Yiping & Wang, Qi, 2024. "Data labeling through the centralities of co-reference networks improves the classification accuracy of scientific papers," Journal of Informetrics, Elsevier, vol. 18(2).
    18. 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.
    19. Li Zhai & Xiujuan Li & Xiangbin Yan & Weiguo Fan, 2014. "Evolutionary analysis of collaboration networks in the field of information systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1657-1677, December.
    20. Alireza Abbasi, 2013. "h-Type hybrid centrality measures for weighted networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 633-640, August.

    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:eee:infome:v:12:y:2018:i:1:p:299-314. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.