IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v548y2020ics0378437119321533.html
   My bibliography  Save this article

Identifying significant edges via neighborhood information

Author

Listed:
  • Zhao, Na
  • Li, Jie
  • Wang, Jian
  • Li, Tong
  • Yu, Yong
  • Zhou, Tao

Abstract

The heterogeneous nature of real networks implies that different edges play different roles in network structure and functions, and thus to identify significant edges is of high value in both theoretical studies and practical applications. We propose the so-called second-order neighborhood (SN) index to quantify an edge’s significance in a network. We apply the edge percolation process to measure the significance of edges in maintaining the network connectivity. We compare the SN index with many other benchmark methods based on 15 real networks, showing that the proposed SN index outperforms other well-known methods.

Suggested Citation

  • Zhao, Na & Li, Jie & Wang, Jian & Li, Tong & Yu, Yong & Zhou, Tao, 2020. "Identifying significant edges via neighborhood information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    • Handle: RePEc:eee:phsmap:v:548:y:2020:i:c:s0378437119321533
    DOI: 10.1016/j.physa.2019.123877
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119321533
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.123877?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. Jian Gao & Yi-Cheng Zhang & Tao Zhou, 2019. "Computational Socioeconomics," Papers 1905.06166, arXiv.org.
    2. Robert M. May & Simon A. Levin & George Sugihara, 2008. "Ecology for bankers," Nature, Nature, vol. 451(7181), pages 893-894, February.
    3. Cristopher Moore & M. E. J. Newman, 2000. "Epidemics and Percolation in Small-World Networks," Working Papers 00-01-002, Santa Fe Institute.
    4. Ruiqi Li & Lei Dong & Jiang Zhang & Xinran Wang & Wen-Xu Wang & Zengru Di & H. Eugene Stanley, 2017. "Simple spatial scaling rules behind complex cities," Nature Communications, Nature, vol. 8(1), pages 1-7, December.
    5. Duan, Boping & Liu, Jing & Zhou, Mingxing & Ma, Liangliang, 2016. "A comparative analysis of network robustness against different link attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 144-153.
    6. Caldarelli, Guido, 2007. "Scale-Free Networks: Complex Webs in Nature and Technology," OUP Catalogue, Oxford University Press, number 9780199211517.
    7. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    8. Mehri, Ali & Darooneh, Amir H. & Shariati, Ashrafalsadat, 2012. "The complex networks approach for authorship attribution of books," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2429-2437.
    9. Zhou, Ming-Yang & Xiong, Wen-Man & Wu, Xiang-Yang & Zhang, Yu-Xia & Liao, Hao, 2018. "Overlapping influence inspires the selection of multiple spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 76-83.
    10. 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.
    11. Pablo M. Gleiser & Leon Danon, 2003. "Community Structure In Jazz," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 565-573.
    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. Mukashov, A., 2023. "Parameter uncertainty in policy planning models: Using portfolio management methods to choose optimal policies under world market volatility," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 187-202.
    2. Han, Jihui & Zhang, Ge & Dong, Gaogao & Zhao, Longfeng & Shi, Yuefeng & Zou, Yijiang, 2024. "Exact analysis of generalized degree-based percolation without memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 642(C).

    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. Xu, Shuang & Wang, Pei, 2017. "Identifying important nodes by adaptive LeaderRank," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 654-664.
    2. Tomovski, Igor & Kocarev, Ljupčo, 2015. "Network topology inference from infection statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 272-285.
    3. Andrey Sokolov & Rachel Webster & Andrew Melatos & Tien Kieu, 2012. "Loan and nonloan flows in the Australian interbank network," Papers 1202.3182, arXiv.org.
    4. Foti, Nicholas J. & Pauls, Scott & Rockmore, Daniel N., 2013. "Stability of the World Trade Web over time – An extinction analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1889-1910.
    5. Liu, Shuxin & Ji, Xinsheng & Liu, Caixia & Bai, Yi, 2017. "Extended resource allocation index for link prediction of complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 174-183.
    6. Sokolov, Andrey & Webster, Rachel & Melatos, Andrew & Kieu, Tien, 2012. "Loan and nonloan flows in the Australian interbank network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2867-2882.
    7. Tiziano Squartini & Guido Caldarelli & Giulio Cimini & Andrea Gabrielli & Diego Garlaschelli, 2018. "Reconstruction methods for networks: the case of economic and financial systems," Papers 1806.06941, arXiv.org.
    8. Kumar, Ajay & Singh, Shashank Sheshar & Singh, Kuldeep & Biswas, Bhaskar, 2020. "Link prediction techniques, applications, and performance: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    9. Yin, Likang & Zheng, Haoyang & Bian, Tian & Deng, Yong, 2017. "An evidential link prediction method and link predictability based on Shannon entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 699-712.
    10. Pawe{l} Smaga & Mateusz Wili'nski & Piotr Ochnicki & Piotr Arendarski & Tomasz Gubiec, 2016. "Can banks default overnight? Modeling endogenous contagion on O/N interbank market," Papers 1603.05142, arXiv.org.
    11. You, Tao & Cheng, Hui-Min & Ning, Yi-Zi & Shia, Ben-Chang & Zhang, Zhong-Yuan, 2016. "Community detection in complex networks using density-based clustering algorithm and manifold learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 221-230.
    12. Xu-Wen Wang & Lorenzo Madeddu & Kerstin Spirohn & Leonardo Martini & Adriano Fazzone & Luca Becchetti & Thomas P. Wytock & István A. Kovács & Olivér M. Balogh & Bettina Benczik & Mátyás Pétervári & Be, 2023. "Assessment of community efforts to advance network-based prediction of protein–protein interactions," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    13. Zhang, Peng & Qiu, Dan & Zeng, An & Xiao, Jinghua, 2018. "A comprehensive comparison of network similarities for link prediction and spurious link elimination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 97-105.
    14. Zhou, Wen & Jia, Yifan, 2017. "Predicting links based on knowledge dissemination in complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 561-568.
    15. Li, Hanwen & Shang, Qiuyan & Deng, Yong, 2021. "A generalized gravity model for influential spreaders identification in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    16. Hesamipour, Sajjad & Balafar, Mohammad Ali, 2019. "A new method for detecting communities and their centers using the Adamic/Adar Index and game theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    17. Lee, Yan-Li & Dong, Qiang & Zhou, Tao, 2021. "Link prediction via controlling the leading eigenvector," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    18. Mishra, Shivansh & Singh, Shashank Sheshar & Kumar, Ajay & Biswas, Bhaskar, 2022. "ELP: Link prediction in social networks based on ego network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    19. Liao, Hao & Zeng, An & Zhang, Yi-Cheng, 2015. "Predicting missing links via correlation between nodes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 216-223.
    20. Fei, Liguo & Zhang, Qi & Deng, Yong, 2018. "Identifying influential nodes in complex networks based on the inverse-square law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1044-1059.

    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:phsmap:v:548:y:2020:i:c:s0378437119321533. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.