IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v187y2024ics0960077924009007.html
   My bibliography  Save this article

Strategic node identification in complex network dynamics

Author

Listed:
  • Nikougoftar, Elaheh

Abstract

Detecting significant nodes in intricate networks is essential for various purposes, including market advertising, rumor management, and predicting scientific publications. Existing algorithms, from basic degree methods to more complex approaches, have been developed, but there is a need for a more robust solution. Traditional methods often focus on local network details, neglecting global aspects. This study introduces a network structure entropy-based node importance ranking method that considers both local and global information. The method’s efficacy is validated through comparisons with three benchmarks, showcasing strong performance on two real-world datasets. Further work could explore scalability and applicability in dynamic scenarios.

Suggested Citation

  • Nikougoftar, Elaheh, 2024. "Strategic node identification in complex network dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:chsofr:v:187:y:2024:i:c:s0960077924009007
    DOI: 10.1016/j.chaos.2024.115348
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077924009007
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2024.115348?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. Xu, Guiqiong & Meng, Lei, 2023. "A novel algorithm for identifying influential nodes in complex networks based on local propagation probability model," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Wang, Xiaojie & Slamu, Wushour & Guo, Wenqiang & Wang, Sixiu & Ren, Yan, 2022. "A novel semi local measure of identifying influential nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    3. Qi Zhang & Meizhu Li & Yong Deng, 2016. "A new structure entropy of complex networks based on nonextensive statistical mechanics," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(10), pages 1-12, October.
    4. Lei, Mingli & Cheong, Kang Hao, 2022. "Node influence ranking in complex networks: A local structure entropy approach," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    5. Harold Guetzkow & Herbert A. Simon, 1955. "The Impact of Certain Communication Nets Upon Organization and Performance in Task-Oriented Groups," Management Science, INFORMS, vol. 1(3-4), pages 233-250, 04-07.
    6. Wang, Min & Li, Wanchun & Guo, Yuning & Peng, Xiaoyan & Li, Yingxiang, 2020. "Identifying influential spreaders in complex networks based on improved k-shell method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    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. Wang, Peng & Ling, Guang & Zhao, Pei & Pan, Wenqiu & Ge, Ming-Feng, 2024. "Identification of important nodes in multi-layer hypergraphs based on fuzzy gravity model and node centrality distribution characteristics," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).
    2. Zhao, Jie & Wang, Zhen & Yu, Dengxiu & Cao, Jinde & Cheong, Kang Hao, 2024. "Swarm intelligence for protecting sensitive identities in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    3. Jesse Shore & Ethan Bernstein & David Lazer, 2014. "Facts and Figuring: An Experimental Investigation of Network Structure and Performance in Information and Solution Spaces," Harvard Business School Working Papers 14-075, Harvard Business School, revised Jun 2014.
    4. Chaharborj, Sarkhosh Seddighi & Nabi, Khondoker Nazmoon & Feng, Koo Lee & Chaharborj, Shahriar Seddighi & Phang, Pei See, 2022. "Controlling COVID-19 transmission with isolation of influential nodes," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    5. Andrew Mao & Winter Mason & Siddharth Suri & Duncan J Watts, 2016. "An Experimental Study of Team Size and Performance on a Complex Task," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-22, April.
    6. Swanson, Earl R., 1979. "Working with Other Disciplines," 1979 Annual Meeting, July 29-August 1, Pullman, Washington 278218, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Wu, Yali & Dong, Ang & Ren, Yuanguang & Jiang, Qiaoyong, 2023. "Identify influential nodes in complex networks: A k-orders entropy-based method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    8. Nicolai j. Foss & Lars Frederiksen & Francesco Rullani, 2016. "Problem‐formulation and problem‐solving in self‐organized communities: How modes of communication shape project behaviors in the free open‐source software community," Strategic Management Journal, Wiley Blackwell, vol. 37(13), pages 2589-2610, December.
    9. Marlo Raveendran & Phanish Puranam & Massimo Warglien, 2016. "Object Salience in the Division of Labor: Experimental Evidence," Management Science, INFORMS, vol. 62(7), pages 2110-2128, July.
    10. Uyen-Phuong Nguyen & Philip Hallinger, 2020. "Assessing the Distinctive Contributions of Simulation & Gaming to the Literature, 1970-2019: A Bibliometric Review," Simulation & Gaming, , vol. 51(6), pages 744-769, December.
    11. Tian, Yang & Tian, Hui & Cui, Qimei & Zhu, Xuzhen, 2024. "Phase transition phenomena in social propagation with dynamic fashion tendency and individual contact," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    12. Hossain, Liaquat & Murshed, Shahriar Tanvir & Uddin, Shahadat, 2013. "Communication network dynamics during organizational crisis," Journal of Informetrics, Elsevier, vol. 7(1), pages 16-35.
    13. Ramirez-Arellano, Aldo & Hernández-Simón, Luis Manuel & Bory-Reyes, Juan, 2020. "A box-covering Tsallis information dimension and non-extensive property of complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    14. Yin, Rongrong & Li, Linhui & Wang, Yumeng & Lang, Chun & Hao, Zhenyang & Zhang, Le, 2024. "Identifying critical nodes in complex networks based on distance Laplacian energy," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    15. Abbasi, Alireza & Altmann, Jörn & Hossain, Liaquat, 2011. "Identifying the effects of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance measures and social network analysis measures," Journal of Informetrics, Elsevier, vol. 5(4), pages 594-607.
    16. Jesse Shore & Ethan Bernstein & David Lazer, 2015. "Facts and Figuring: An Experimental Investigation of Network Structure and Performance in Information and Solution Spaces," Organization Science, INFORMS, vol. 26(5), pages 1432-1446, October.
    17. Linda Argote & Brandy L. Aven & Jonathan Kush, 2018. "The Effects of Communication Networks and Turnover on Transactive Memory and Group Performance," Organization Science, INFORMS, vol. 29(2), pages 191-206, April.
    18. Ma, Xiaoxue & Deng, Wanyi & Qiao, Weiliang & Lan, He, 2022. "A methodology to quantify the risk propagation of hazardous events for ship grounding accidents based on directed CN," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    19. repec:zbw:rwirep:0332 is not listed on IDEAS
    20. Liu, Panfeng & Li, Longjie & Fang, Shiyu & Yao, Yukai, 2021. "Identifying influential nodes in social networks: A voting approach," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    21. Li, Meizhu & Zhang, Qi & Deng, Yong, 2018. "Evidential identification of influential nodes in network of networks," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 283-296.

    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:187:y:2024:i:c:s0960077924009007. 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.