IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v161y2022ics0960077922003502.html
   My bibliography  Save this article

The subnetwork investigation of scale-free networks based on the self-similarity

Author

Listed:
  • Wang, Wenting
  • Shi, Shijie
  • Fu, Xianghua

Abstract

The scale-free network with self-similarity is an essential data structure widely used in social networks and bioinformatics. The subnetwork investigation of large-scale networks has attracted attention in many applications. Traditional methods are computationally complexity and time-consuming. A new methodology needs to handle the computational complexity challenge from large-scale network datasets. In this paper, we develop a series of edge-based subnetwork investigation algorithms: HEPS-1 and HEPS-2. We investigate the relations between edges and their edge neighbours caused by the reconcile of scale-free and self-similarity. Then, we determine the edges for the subnetwork. In this way, we sample the networks while keeping the original statistical characters. The computational complexity is low. The effectiveness of sampling is enhanced.

Suggested Citation

  • Wang, Wenting & Shi, Shijie & Fu, Xianghua, 2022. "The subnetwork investigation of scale-free networks based on the self-similarity," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    • Handle: RePEc:eee:chsofr:v:161:y:2022:i:c:s0960077922003502
    DOI: 10.1016/j.chaos.2022.112140
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077922003502
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2022.112140?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. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    2. Chaoming Song & Shlomo Havlin & Hernán A. Makse, 2005. "Self-similarity of complex networks," Nature, Nature, vol. 433(7024), pages 392-395, January.
    3. Faraway, Julian J. & Augustin, Nicole H., 2018. "When small data beats big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 142-145.
    4. Jarod Y. L. Lee & James J. Brown & Louise M. Ryan, 2017. "Sufficiency Revisited: Rethinking Statistical Algorithms in the Big Data Era," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 202-208, July.
    5. Qi Gao & Xintong Ding & Feng Pan & Weixing Li, 2014. "An improved sampling method of complex network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(05), pages 1-11.
    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. Yang, Qing-Lin & Wang, Li-Fu & Zhao, Guo-Tao & Guo, Ge, 2020. "A coarse graining algorithm based on m-order degree in complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    2. Yao, Jialing & Sun, Bingbin & Xi, lifeng, 2019. "Fractality of evolving self-similar networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 211-216.
    3. Rohith D. Vallam & C.A. Subramanian & Ramasuri Narayanam & Y. Narahari & N. Srinath, 2014. "Strategic Network Formation with Localized Pay-offs," Studies in Microeconomics, , vol. 2(1), pages 63-119, June.
    4. Jianxi Gao & Xueming Liu & Daqing Li & Shlomo Havlin, 2015. "Recent Progress on the Resilience of Complex Networks," Energies, MDPI, vol. 8(10), pages 1-24, October.
    5. Feng, Jia & Li, Xiamiao & Mao, Baohua & Xu, Qi & Bai, Yun, 2017. "Weighted complex network analysis of the Beijing subway system: Train and passenger flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 213-223.
    6. Li, Chunguang, 2009. "Memorizing morph patterns in small-world neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(2), pages 240-246.
    7. Zheng, Song & Yuan, Liguo, 2019. "Nonperiodically intermittent pinning synchronization of complex-valued complex networks with non-derivative and derivative coupling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 587-605.
    8. Emerson, Isaac Arnold & Amala, Arumugam, 2017. "Protein contact maps: A binary depiction of protein 3D structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 782-791.
    9. Wu, Zhenxing & Lu, Xi & Deng, Yong, 2015. "Image edge detection based on local dimension: A complex networks approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 440(C), pages 9-18.
    10. Zhenpeng Li & Ling Ma & Simin Chi & Xu Qian, 2022. "Structural Balance under Weight Evolution of Dynamic Signed Network," Mathematics, MDPI, vol. 10(9), pages 1-21, April.
    11. Bon Joshua J. & Baffour Bernard & Spallek Melanie & Haynes Michele, 2020. "Analysing Sensitive Data from Dynamically-Generated Overlapping Contingency Tables," Journal of Official Statistics, Sciendo, vol. 36(2), pages 275-296, June.
    12. Xie, Wen-Jie & Zhou, Wei-Xing, 2011. "Horizontal visibility graphs transformed from fractional Brownian motions: Topological properties versus the Hurst index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3592-3601.
    13. Dan Braha & Yaneer Bar-Yam, 2007. "The Statistical Mechanics of Complex Product Development: Empirical and Analytical Results," Management Science, INFORMS, vol. 53(7), pages 1127-1145, July.
    14. Faedo, Nicolás & García-Violini, Demián & Ringwood, John V., 2021. "Controlling synchronization in a complex network of nonlinear oscillators via feedback linearisation and H∞-control," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    15. Yu-Hsiang Fu & Chung-Yuan Huang & Chuen-Tsai Sun, 2017. "A community detection algorithm using network topologies and rule-based hierarchical arc-merging strategies," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-30, November.
    16. Zhou, Wei-Xing & Jiang, Zhi-Qiang & Sornette, Didier, 2007. "Exploring self-similarity of complex cellular networks: The edge-covering method with simulated annealing and log-periodic sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 741-752.
    17. Paul Sheridan & Yuichi Yagahara & Hidetoshi Shimodaira, 2008. "A preferential attachment model with Poisson growth for scale-free networks," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 747-761, December.
    18. Ni, Shunjiang & Weng, Wenguo & Zhang, Hui, 2011. "Modeling the effects of social impact on epidemic spreading in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4528-4534.
    19. Xiao‐Bing Hu & Hang Li & XiaoMei Guo & Pieter H. A. J. M. van Gelder & Peijun Shi, 2019. "Spatial Vulnerability of Network Systems under Spatially Local Hazards," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 162-179, January.
    20. Werner, Gerhard, 2013. "Consciousness viewed in the framework of brain phase space dynamics, criticality, and the Renormalization Group," Chaos, Solitons & Fractals, Elsevier, vol. 55(C), pages 3-12.

    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:chsofr:v:161:y:2022:i:c:s0960077922003502. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.