IDEAS home Printed from https://ideas.repec.org/a/wsi/acsxxx/v22y2019i07n08ns0219525919500140.html
   My bibliography  Save this article

Control Contribution Identifies Top Driver Nodes In Complex Networks

Author

Listed:
  • YAN ZHANG

    (Chair of Systems Design, ETH Zurich, Weinbergstrasse 58, 8092 Zurich, Switzerland)

  • ANTONIOS GARAS

    (Chair of Systems Design, ETH Zurich, Weinbergstrasse 58, 8092 Zurich, Switzerland)

  • FRANK SCHWEITZER

    (Chair of Systems Design, ETH Zurich, Weinbergstrasse 58, 8092 Zurich, Switzerland)

Abstract

We propose a new measure to quantify the impact of a node i in controlling a directed network. This measure, called “control contribution” 𝒞i, combines the probability for node i to appear in a set of driver nodes and the probability for other nodes to be controlled by i. To calculate 𝒞i, we propose an optimization method based on random samples of minimum sets of drivers. Using real-world and synthetic networks, we find very broad distributions of Ci. Ranking nodes according to their Ci values allows us to identify the top driver nodes that can control most of the network. We show that this ranking is superior to rankings based on other control-based measures. We find that control contribution indeed contains new information that cannot be traced back to degree, control capacity or control range of a node.

Suggested Citation

  • Yan Zhang & Antonios Garas & Frank Schweitzer, 2019. "Control Contribution Identifies Top Driver Nodes In Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(07n08), pages 1-15, December.
    • Handle: RePEc:wsi:acsxxx:v:22:y:2019:i:07n08:n:s0219525919500140
    DOI: 10.1142/S0219525919500140
    as

    Download full text from publisher

    File URL: https://www.worldscientific.com/doi/abs/10.1142/S0219525919500140
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219525919500140?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. Stefania Vitali & James B Glattfelder & Stefano Battiston, 2011. "The Network of Global Corporate Control," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-6, October.
    2. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2011. "Controllability of complex networks," Nature, Nature, vol. 473(7346), pages 167-173, May.
    3. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2012. "Control Centrality and Hierarchical Structure in Complex Networks," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-7, September.
    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. Aming Li & Yang-Yu Liu, 2020. "Controlling Network Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(07n08), pages 1-19, February.
    2. Yan Zhang & Frank Schweitzer, 2021. "Quantifying the importance of firms by means of reputation and network control," Papers 2101.05010, arXiv.org.
    3. Frank Schweitzer & Giona Casiraghi & Mario V. Tomasello & David Garcia, 2020. "Fragile, yet resilient: Adaptive decline in a collaboration network of firms," Papers 2011.13369, arXiv.org.
    4. Yu, Xiaoyao & Liang, Yongqing & Wang, Xiaomeng & Jia, Tao, 2021. "The network asymmetry caused by the degree correlation and its effect on the bimodality in control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(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. Li, Sheng & Liu, Wenwen & Wu, Ruizi & Li, Junli, 2023. "An adaptive attack model to network controllability," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    2. Li, Jian & Dueñas-Osorio, Leonardo & Chen, Changkun & Shi, Congling, 2016. "Connectivity reliability and topological controllability of infrastructure networks: A comparative assessment," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 24-33.
    3. Li, Xin-Feng & Lu, Zhe-Ming, 2016. "Optimizing the controllability of arbitrary networks with genetic algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 422-433.
    4. Nie, Sen & Wang, Xuwen & Wang, Binghong, 2015. "Effect of degree correlation on exact controllability of multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 98-102.
    5. Ding, Jin & Lu, Yong-Zai & Chu, Jian, 2013. "Studies on controllability of directed networks with extremal optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6603-6615.
    6. Cai, Ning, 2017. "On quantitatively measuring controllability of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 282-292.
    7. Babak Ravandi & Forough S. Ansari & Fatma Mili, 2020. "Controllability Analysis Of Complex Networks Using Statistical Random Sampling," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(07n08), pages 1-15, January.
    8. Yin, Hongli & Zhang, Siying, 2016. "Minimum structural controllability problems of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 467-476.
    9. Xiaoqian Sun & Sebastian Wandelt & Xianbin Cao, 2017. "On Node Criticality in Air Transportation Networks," Networks and Spatial Economics, Springer, vol. 17(3), pages 737-761, September.
    10. Yang, Xu-Hua & Chen, Guang & Chen, Sheng-Yong, 2013. "The impact of connection density on scale-free distribution in random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2547-2554.
    11. Hu, Ying & Yu, Yang & Mardani, Abbas, 2021. "Selection of carbon emissions control industries in China: An approach based on complex networks control perspective," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    12. Han, Fangyuan & Zio, Enrico, 2019. "A multi-perspective framework of analysis of critical infrastructures with respect to supply service, controllability and topology," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 1-13.
    13. Caetano, Marco Antonio Leonel & Yoneyama, Takashi, 2015. "An autocatalytic network model for stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 122-127.
    14. Aming Li & Yang-Yu Liu, 2020. "Controlling Network Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(07n08), pages 1-19, February.
    15. Cem Iskender Aydin & Begum Ozkaynak & Beatriz Rodríguez-Labajos & Taylan Yenilmez, 2017. "Network effects in environmental justice struggles: An investigation of conflicts between mining companies and civil society organizations from a network perspective," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-20, July.
    16. Hayato Goto & Eduardo Viegas & Hideki Takayasu & Misako Takayasu & Henrik Jeldtoft Jensen, 2019. "Dynamics of essential interaction between firms on financial reports," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-16, December.
    17. Abhijit Chakraborty & Tobias Reisch & Christian Diem & Pablo Astudillo-Estévez & Stefan Thurner, 2024. "Inequality in economic shock exposures across the global firm-level supply network," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    18. Andreas Koulouris & Ioannis Katerelos & Theodore Tsekeris, 2013. "Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(1), pages 51-70.
    19. Hayafumi Watanabe, 2014. "Mean Field Approximation for Biased Diffusion on Japanese Inter-Firm Trading Network," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-5, March.
    20. He, He & Yang, Bo & Hu, Xiaoming, 2016. "Exploring community structure in networks by consensus dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 342-353.

    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:wsi:acsxxx:v:22:y:2019:i:07n08:n:s0219525919500140. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/acs/acs.shtml .

    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.