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h-Degree as a basic measure in weighted networks

Author

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  • Zhao, Star X.
  • Rousseau, Ronald
  • Ye, Fred Y.

Abstract

We introduce the h-degree of a node as a basic indicator for weighted networks. The h-degree (dh) of a node is the number dh if this node has at least dh links with other nodes and the strength of each of these links is greater than or equal to dh. Based on the notion of h-degree other notions are developed such as h-centrality and h-centralization, leading to a new set of indicators characterizing nodes in a network.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:infome:v:5:y:2011:i:4:p:668-677
    DOI: 10.1016/j.joi.2011.06.005
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    References listed on IDEAS

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    1. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 2000. "Scale-free characteristics of random networks: the topology of the world-wide web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 281(1), pages 69-77.
    2. Rodriguez, Marko A. & Pepe, Alberto, 2008. "On the relationship between the structural and socioacademic communities of a coauthorship network," Journal of Informetrics, Elsevier, vol. 2(3), pages 195-201.
    3. Chen, P. & Redner, S., 2010. "Community structure of the physical review citation network," Journal of Informetrics, Elsevier, vol. 4(3), pages 278-290.
    4. Jin-Qing Fang, 2010. "Network Science—Theory and Application," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(6), pages 1297-1298, June.
    5. Fred Y. Ye, 2011. "A unification of three models for the h-index," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(1), pages 205-207, January.
    6. Schubert, András & Glänzel, Wolfgang, 2007. "A systematic analysis of Hirsch-type indices for journals," Journal of Informetrics, Elsevier, vol. 1(3), pages 179-184.
    7. 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.
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    Citations

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    Cited by:

    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. Zivar Sabaghinejad & Farideh Osareh & Fatima Baji & Parastou Parsaei Mohammadi, 2016. "Estimating the partnership ability of Scientometrics journal authors based on WoS from 2001 to 2013 according to ϕ-index1," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 73-84, October.
    3. 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).
    4. R. G. Raj & A. N. Zainab, 2012. "Relative measure index: a metric to measure the quality of journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 305-317, November.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. András Schubert, 2012. "A Hirsch-type index of co-author partnership ability," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 303-308, April.
    12. Guillaume Cabanac, 2013. "Experimenting with the partnership ability φ-index on a million computer scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 1-9, July.
    13. Sima Sobhi-Givi & Azadeh Khazali & Hashem Kalbkhani & Mahrokh G. Shayesteh & Vahid Solouk, 2018. "Joint mode selection and resource allocation in D2D communication based underlaying cellular networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(1), pages 47-62, January.
    14. 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.
    15. András Schubert, 2015. "Rescaling the h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1647-1653, February.
    16. Alireza Abbasi, 2013. "h-Type hybrid centrality measures for weighted networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 633-640, August.

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