IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v465y2017icp701-713.html
   My bibliography  Save this article

Link Influence Entropy

Author

Listed:
  • Singh, Priti
  • Chakraborty, Abhishek
  • Manoj, B.S.

Abstract

In this paper we propose a new metric, Link Influence Entropy (LInE), which describes importance of each node based on the influence of each link present in a network. Influence of a link can neither be effectively estimated using betweenness centrality nor using degree based probability measures. The proposed LInE metric which provides an effective way to estimate the influence of a link in the network and incorporates this influence to identify nodal characteristics, performs better compared to degree based entropy. We found that LInE can differentiate various network types which degree-based or betweenness centrality based node influence metrics cannot. Our findings show that spatial wireless networks and regular grid networks, respectively, have lowest and highest LInE values. Finally, performance analysis of LInE is carried out on a real-world network as well as on a wireless mesh network testbed to study the influence of our metric as well as influence stability of nodes in dynamic networks.

Suggested Citation

  • Singh, Priti & Chakraborty, Abhishek & Manoj, B.S., 2017. "Link Influence Entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 701-713.
    • Handle: RePEc:eee:phsmap:v:465:y:2017:i:c:p:701-713
    DOI: 10.1016/j.physa.2016.08.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116305350
    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.2016.08.019?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. Xiao, Yang-Hua & Wu, Wen-Tao & Wang, Hui & Xiong, Momiao & Wang, Wei, 2008. "Symmetry-based structure entropy of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2611-2619.
    2. 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.
    3. Wu, Liusan & Tan, Qingmei & Zhang, Yuehui, 2013. "Network connectivity entropy and its application on network connectivity reliability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5536-5541.
    4. 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.
    5. Schaub, Michael T. & Lehmann, Jã–Rg & Yaliraki, Sophia N. & Barahona, Mauricio, 2014. "Structure of complex networks: Quantifying edge-to-edge relations by failure-induced flow redistribution," Network Science, Cambridge University Press, vol. 2(1), pages 66-89, April.
    6. Wei, Daijun & Deng, Xinyang & Zhang, Xiaoge & Deng, Yong & Mahadevan, Sankaran, 2013. "Identifying influential nodes in weighted networks based on evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2564-2575.
    7. Wang, Bing & Tang, Huanwen & Guo, Chonghui & Xiu, Zhilong, 2006. "Entropy optimization of scale-free networks’ robustness to random failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 591-596.
    8. Demetrius, Lloyd & Manke, Thomas, 2005. "Robustness and network evolution—an entropic principle," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 682-696.
    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. Deng, Xinyang & Deng, Yong, 2014. "On the axiomatic requirement of range to measure uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 163-168.
    2. 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.
    3. Zhu, Hengmin & Yin, Xicheng & Ma, Jing & Hu, Wei, 2016. "Identifying the main paths of information diffusion in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 320-328.
    4. Ni, Chengzhang & Yang, Jun & Kong, Demei, 2020. "Sequential seeding strategy for social influence diffusion with improved entropy-based centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    5. 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.
    6. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Shokrollahi, Arman, 2015. "Improving detection of influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 833-845.
    7. Chen, Yahong & Li, Jinlin & Huang, He & Ran, Lun & Hu, Yusheng, 2017. "Encouraging information sharing to boost the name-your-own-price auction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 108-117.
    8. Hu, Jiantao & Du, Yuxian & Mo, Hongming & Wei, Daijun & Deng, Yong, 2016. "A modified weighted TOPSIS to identify influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 73-85.
    9. Liu, Jie & Li, Yunpeng & Ruan, Zichan & Fu, Guangyuan & Chen, Xiaowu & Sadiq, Rehan & Deng, Yong, 2015. "A new method to construct co-author networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 29-39.
    10. Du, Yuxian & Gao, Cai & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2014. "A new method of identifying influential nodes in complex networks based on TOPSIS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 57-69.
    11. Salavati, Chiman & Abdollahpouri, Alireza & Manbari, Zhaleh, 2018. "BridgeRank: A novel fast centrality measure based on local structure of the network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 635-653.
    12. Wang, Yanhui & Bi, Lifeng & Lin, Shuai & Li, Man & Shi, Hao, 2017. "A complex network-based importance measure for mechatronics systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 180-198.
    13. Jincheng Jiang & Jinsong Chen & Wei Tu & Chisheng Wang, 2019. "A Novel Effective Indicator of Weighted Inter-City Human Mobility Networks to Estimate Economic Development," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
    14. Umut Yilmaz Cetinkaya & Erkan Erdil, 2015. "Cohesion and Competition of Europe: Policy Suggestions from The Perspective of Network and Entropy," STPS Working Papers 1505, STPS - Science and Technology Policy Studies Center, Middle East Technical University, revised Dec 2015.
    15. Umut Yilmaz Cetinkaya & Erkan Erdil, 2016. "Cohesion and Competition of Europe: Innovation Policy from the Perspective of Networks and Entropy," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 10(4), pages 7-24.
    16. 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.
    17. Su, Xiaoyan & Mahadevan, Sankaran & Xu, Peida & Deng, Yong, 2014. "Inclusion of task dependence in human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 128(C), pages 41-55.
    18. Feng-Que Pei & Dong-Bo Li & Yi-Fei Tong & Fei He, 2017. "Process service quality evaluation based on Dempster-Shafer theory and support vector machine," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-16, December.
    19. Ma, Ling-ling & Ma, Chuang & Zhang, Hai-Feng & Wang, Bing-Hong, 2016. "Identifying influential spreaders in complex networks based on gravity formula," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 205-212.
    20. Cai Gao & Xin Lan & Xiaoge Zhang & Yong Deng, 2013. "A Bio-Inspired Methodology of Identifying Influential Nodes in Complex Networks," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.

    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:465:y:2017:i:c:p:701-713. 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.