IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-47248-x.html
   My bibliography  Save this article

Reconstructing the evolution history of networked complex systems

Author

Listed:
  • Junya Wang

    (Sun Yat-sen University)

  • Yi-Jiao Zhang

    (Southern University of Science and Technology)

  • Cong Xu

    (Southern University of Science and Technology)

  • Jiaze Li

    (Maastricht University)

  • Jiachen Sun

    (Tencent Inc.)

  • Jiarong Xie

    (Beijing Normal University
    Beijing Normal University)

  • Ling Feng

    (Technology and Research (A*STAR)
    National University of Singapore)

  • Tianshou Zhou

    (Sun Yat-sen University)

  • Yanqing Hu

    (Southern University of Science and Technology
    Southern University of Science and Technology)

Abstract

The evolution processes of complex systems carry key information in the systems’ functional properties. Applying machine learning algorithms, we demonstrate that the historical formation process of various networked complex systems can be extracted, including protein-protein interaction, ecology, and social network systems. The recovered evolution process has demonstrations of immense scientific values, such as interpreting the evolution of protein-protein interaction network, facilitating structure prediction, and particularly revealing the key co-evolution features of network structures such as preferential attachment, community structure, local clustering, degree-degree correlation that could not be explained collectively by previous theories. Intriguingly, we discover that for large networks, if the performance of the machine learning model is slightly better than a random guess on the pairwise order of links, reliable restoration of the overall network formation process can be achieved. This suggests that evolution history restoration is generally highly feasible on empirical networks.

Suggested Citation

  • Junya Wang & Yi-Jiao Zhang & Cong Xu & Jiaze Li & Jiachen Sun & Jiarong Xie & Ling Feng & Tianshou Zhou & Yanqing Hu, 2024. "Reconstructing the evolution history of networked complex systems," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47248-x
    DOI: 10.1038/s41467-024-47248-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-47248-x
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-47248-x?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
    ---><---

    References listed on IDEAS

    as
    1. David Liben‐Nowell & Jon Kleinberg, 2007. "The link‐prediction problem for social networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(7), pages 1019-1031, May.
    2. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    3. José M. Montoya & Stuart L. Pimm & Ricard V. Solé, 2006. "Ecological networks and their fragility," Nature, Nature, vol. 442(7100), pages 259-264, July.
    4. Fragkiskos Papadopoulos & Maksim Kitsak & M. Ángeles Serrano & Marián Boguñá & Dmitri Krioukov, 2012. "Popularity versus similarity in growing networks," Nature, Nature, vol. 489(7417), pages 537-540, September.
    5. Peter Emerson, 2013. "The original Borda count and partial voting," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 40(2), pages 353-358, February.
    6. Guillermo Garc'ia-P'erez & Mari'an Bogu~n'a & Antoine Allard & M. 'Angeles Serrano, 2015. "The hidden hyperbolic geometry of international trade: World Trade Atlas 1870-2013," Papers 1512.02233, arXiv.org, revised May 2016.
    7. Andreas Wagner, 2001. "The Yeast Protein Interaction Network Evolves Rapidly and Contains Few Redundant Duplicate Genes," Working Papers 01-04-022, Santa Fe Institute.
    8. Jiarong Xie & Fanhui Meng & Jiachen Sun & Xiao Ma & Gang Yan & Yanqing Hu, 2021. "Detecting and modelling real percolation and phase transitions of information on social media," Nature Human Behaviour, Nature, vol. 5(9), pages 1161-1168, September.
    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. Leto Peel & Tiago P. Peixoto & Manlio De Domenico, 2022. "Statistical inference links data and theory in network science," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Maksim Kitsak & Alexander Ganin & Ahmed Elmokashfi & Hongzhu Cui & Daniel A. Eisenberg & David L. Alderson & Dmitry Korkin & Igor Linkov, 2023. "Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    3. Zhenpeng Li & Luo Li, 2023. "The Generation Mechanism of Degree Distribution with Power Exponent >2 and the Growth of Edges in Temporal Social Networks," Mathematics, MDPI, vol. 11(13), pages 1-11, June.
    4. Hanbaek Lyu & Yacoub H. Kureh & Joshua Vendrow & Mason A. Porter, 2024. "Learning low-rank latent mesoscale structures in networks," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Lee, Yan-Li & Dong, Qiang & Zhou, Tao, 2021. "Link prediction via controlling the leading eigenvector," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    6. Robert Jankowski & Antoine Allard & Marián Boguñá & M. Ángeles Serrano, 2023. "The D-Mercator method for the multidimensional hyperbolic embedding of real networks," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Wahid-Ul-Ashraf, Akanda & Budka, Marcin & Musial, Katarzyna, 2019. "How to predict social relationships — Physics-inspired approach to link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1110-1129.
    8. Liat Ayalon & Inbal Yahav, 2019. "Location, location, location: Close ties among older continuing care retirement community residents," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-17, November.
    9. Jeong, Yujin & Park, Inchae & Yoon, Byungun, 2019. "Identifying emerging Research and Business Development (R&BD) areas based on topic modeling and visualization with intellectual property right data," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 655-672.
    10. Huan Wang & Chuang Ma & Han-Shuang Chen & Ying-Cheng Lai & Hai-Feng Zhang, 2022. "Full reconstruction of simplicial complexes from binary contagion and Ising data," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    11. Mónica de Castro-Pardo & Fernando Pérez-Rodríguez & José María Martín-Martín & João C. Azevedo, 2019. "Planning for Democracy in Protected Rural Areas: Application of a Voting Method in a Spanish-Portuguese Reserve," Land, MDPI, vol. 8(10), pages 1-17, October.
    12. Omar A. Alismaiel & Javier Cifuentes-Faura & Waleed Mugahed Al-Rahmi, 2022. "Online Learning, Mobile Learning, and Social Media Technologies: An Empirical Study on Constructivism Theory during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(18), pages 1-15, September.
    13. Vinayak, & Raghuvanshi, Adarsh & kshitij, Avinash, 2023. "Signatures of capacity development through research collaborations in artificial intelligence and machine learning," Journal of Informetrics, Elsevier, vol. 17(1).
    14. Yifei Zhou & Shaoyong Li & Yaping Liu, 2020. "Graph-based Method for App Usage Prediction with Attributed Heterogeneous Network Embedding," Future Internet, MDPI, vol. 12(3), pages 1-16, March.
    15. Jascha-Alexander Koch & Michael Siering, 2019. "The recipe of successful crowdfunding campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(4), pages 661-679, December.
    16. Supriya Tiwari & Pallavi Basu, 2024. "Quasi-randomization tests for network interference," Papers 2403.16673, arXiv.org, revised Oct 2024.
    17. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    18. Karimi, Fatemeh & Lotfi, Shahriar & Izadkhah, Habib, 2021. "Community-guided link prediction in multiplex networks," Journal of Informetrics, Elsevier, vol. 15(4).
    19. Samrachana Adhikari & Beau Dabbs, 2018. "Social Network Analysis in R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 225-253, April.
    20. 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).

    More about this item

    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:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47248-x. 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: 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.