IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v558y2018i7711d10.1038_d41586-018-05444-y.html
   My bibliography  Save this article

Twenty years of network science

Author

Listed:
  • Alessandro Vespignani

Abstract

The idea that everyone in the world is connected to everyone else by just six degrees of separation was explained by the ‘small-world’ network model 20 years ago. What seemed to be a niche finding turned out to have huge consequences.

Suggested Citation

  • Alessandro Vespignani, 2018. "Twenty years of network science," Nature, Nature, vol. 558(7711), pages 528-529, June.
    • Handle: RePEc:nat:nature:v:558:y:2018:i:7711:d:10.1038_d41586-018-05444-y
    DOI: 10.1038/d41586-018-05444-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/d41586-018-05444-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/d41586-018-05444-y?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carlo Mari & Cristiano Baldassari, 2023. "Optimization of mixture models on time series networks encoded by visibility graphs: an analysis of the US electricity market," Computational Management Science, Springer, vol. 20(1), pages 1-23, December.
    2. Boeing, Geoff, 2019. "Street Network Models and Measures for Every U.S. City, County, Urbanized Area, Census Tract, and Zillow-Defined Neighborhood," SocArXiv 7fxjz, Center for Open Science.
    3. Vincent Bouttier & Salomé Leclercq & Renaud Jardri & Sophie Denève, 2024. "A normative approach to radicalization in social networks," Journal of Computational Social Science, Springer, vol. 7(1), pages 1071-1093, April.
    4. Shixuan Liu & Tianle Pu & Li Zeng & Yunfei Wang & Haoxiang Cheng & Zhong Liu, 2024. "Reinforcement Learning-Based Network Dismantling by Targeting Maximum-Degree Nodes in the Giant Connected Component," Mathematics, MDPI, vol. 12(17), pages 1-15, September.
    5. Chen, Wenhao & Li, Jichao & Jiang, Jiang & Chen, Gang, 2022. "Weighted interdependent network disintegration strategy based on Q-learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    6. Iacopo Iacopini & Márton Karsai & Alain Barrat, 2024. "The temporal dynamics of group interactions in higher-order social networks," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    7. Feng, Xiao & He, Shiwei & Li, Guangye & Chi, Jushang, 2021. "Transfer network of high-speed rail and aviation: Structure and critical components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    8. Fang, Yinhai & Xu, Haiyan & Perc, Matjaž & Tan, Qingmei, 2019. "Dynamic evolution of economic networks under the influence of mergers and divestitures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 89-99.
    9. Ana Teresa Santos & Sandro Mendonça, 2022. "The small world of innovation studies: an “editormetrics” perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7471-7486, December.
    10. Daniel Röchert & Manuel Cargnino & German Neubaum, 2022. "Two sides of the same leader: an agent-based model to analyze the effect of ambivalent opinion leaders in social networks," Journal of Computational Social Science, Springer, vol. 5(2), pages 1159-1205, November.
    11. Chulwook Park, 2019. "Network and Agent Dynamics with Evolving Protection against Systemic Risk," Papers 1907.11622, arXiv.org.
    12. Boeing, Geoff, 2020. "Street Network Models and Indicators for Every Urban Area in the World," SocArXiv f2dqc, Center for Open Science.

    More about this item

    Keywords

    Mathematics and computing;

    Statistics

    Access and download statistics

    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:nat:nature:v:558:y:2018:i:7711:d:10.1038_d41586-018-05444-y. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.