IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v468y2017icp434-444.html
   My bibliography  Save this article

Locating the source of spreading in temporal networks

Author

Listed:
  • Huang, Qiangjuan
  • Zhao, Chengli
  • Zhang, Xue
  • Yi, Dongyun

Abstract

The topological structure of many real networks changes with time. Thus, locating the sources of a temporal network is a creative and challenging problem, as the enormous size of many real networks makes it unfeasible to observe the state of all nodes. In this paper, we propose an algorithm to solve this problem, named the backward temporal diffusion process. The proposed algorithm calculates the shortest temporal distance to locate the transmission source. We assume that the spreading process can be modeled as a simple diffusion process and by consensus dynamics. To improve the location accuracy, we also adopt four strategies to select which nodes should be observed by ranking their importance in the temporal network. Our paper proposes a highly accurate method for locating the source in temporal networks and is, to the best of our knowledge, a frontier work in this field. Moreover, our framework has important significance for controlling the transmission of diseases or rumors and formulating immediate immunization strategies.

Suggested Citation

  • Huang, Qiangjuan & Zhao, Chengli & Zhang, Xue & Yi, Dongyun, 2017. "Locating the source of spreading in temporal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 434-444.
    • Handle: RePEc:eee:phsmap:v:468:y:2017:i:c:p:434-444
    DOI: 10.1016/j.physa.2016.10.081
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116307853
    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.2016.10.081?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. Zhesi Shen & Wen-Xu Wang & Ying Fan & Zengru Di & Ying-Cheng Lai, 2014. "Reconstructing propagation networks with natural diversity and identifying hidden sources," Nature Communications, Nature, vol. 5(1), pages 1-10, September.
    2. Huang, Qiangjuan & Zhao, Chengli & Wang, Xiaojie & Zhang, Xue & Yi, Dongyun, 2015. "Predicting the structural evolution of networks by applying multivariate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 470-480.
    3. Cristopher Moore & M. E. J. Newman, 2000. "Epidemics and Percolation in Small-World Networks," Working Papers 00-01-002, Santa Fe Institute.
    4. Chen Liu & Wen-Bo Du & Wen-Xu Wang, 2014. "Particle Swarm Optimization with Scale-Free Interactions," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-8, May.
    5. Xia, Cheng-yi & Wang, Zhen & Sanz, Joaquin & Meloni, Sandro & Moreno, Yamir, 2013. "Effects of delayed recovery and nonuniform transmission on the spreading of diseases in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1577-1585.
    6. Martin Rosvall & Carl T Bergstrom, 2010. "Mapping Change in Large Networks," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-7, January.
    7. Nakamura, Tomomichi & Tanizawa, Toshihiro, 2012. "Networks with time structure from time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4704-4710.
    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. Shi, Chaoyi & Zhang, Qi & Chu, Tianguang, 2022. "Source estimation in continuous-time diffusion networks via incomplete observation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    2. Li, Huichun & Zhang, Xue & Zhao, Chengli, 2021. "Explaining social events through community evolution on temporal networks," Applied Mathematics and Computation, Elsevier, vol. 404(C).
    3. Xiaole Wan & Zhen Zhang & Chi Zhang & Qingchun Meng, 2020. "Stock Market Temporal Complex Networks Construction, Robustness Analysis, and Systematic Risk Identification: A Case of CSI 300 Index," Complexity, Hindawi, vol. 2020, pages 1-19, July.
    4. Gajewski, Ł.G. & Suchecki, K. & Hołyst, J.A., 2019. "Multiple propagation paths enhance locating the source of diffusion in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 34-41.
    5. Paluch, Robert & Gajewski, Łukasz G. & Suchecki, Krzysztof & Hołyst, Janusz A., 2021. "Impact of interactions between layers on source localization in multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(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. Wang, Xin-Wei & Chen, Zhen & Han, Chao, 2016. "Scheduling for single agile satellite, redundant targets problem using complex networks theory," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 125-132.
    2. Liu, Yangyang & Zhao, Chengli & Wang, Xiaojie & Huang, Qiangjuan & Zhang, Xue & Yi, Dongyun, 2016. "The degree-related clustering coefficient and its application to link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 24-33.
    3. Shuhua Chang & Xinyu Wang & Zheng Wang, 2015. "Modeling and Computation of Transboundary Industrial Pollution with Emission Permits Trading by Stochastic Differential Game," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-29, September.
    4. Ganjeh-Ghazvini, Mostafa & Masihi, Mohsen & Ghaedi, Mojtaba, 2014. "Random walk–percolation-based modeling of two-phase flow in porous media: Breakthrough time and net to gross ratio estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 214-221.
    5. Basnarkov, Lasko, 2021. "SEAIR Epidemic spreading model of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    6. Ali Najmi & Taha H. Rashidi & Alireza Abbasi & S. Travis Waller, 2017. "Reviewing the transport domain: an evolutionary bibliometrics and network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 843-865, February.
    7. Pan, Ya-Nan & Lou, Jing-Jing & Han, Xiao-Pu, 2014. "Outbreak patterns of the novel avian influenza (H7N9)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 265-270.
    8. 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.
    9. Jimi Adams & Ryan Light, 2014. "Mapping Interdisciplinary Fields: Efficiencies, Gaps and Redundancies in HIV/AIDS Research," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-13, December.
    10. Greg Morrison & L Mahadevan, 2012. "Discovering Communities through Friendship," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    11. Melissa Haller & David L. Rigby, 2020. "The geographic evolution of optics technologies in the United States, 1976–2010," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1539-1559, December.
    12. Floortje Alkemade & Carolina Castaldi, 2005. "Strategies for the Diffusion of Innovations on Social Networks," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 3-23, February.
    13. Qin, Yang & Zhong, Xiaoxiong & Jiang, Hao & Ye, Yibin, 2015. "An environment aware epidemic spreading model and immune strategy in complex networks," Applied Mathematics and Computation, Elsevier, vol. 261(C), pages 206-215.
    14. Yuchen Pan & Shuai Ding & Wenjuan Fan & Jing Li & Shanlin Yang, 2015. "Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-19, November.
    15. Jiang, Zhongzhou & Liu, Jing & Wang, Shuai, 2016. "Traveling salesman problems with PageRank Distance on complex networks reveal community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 293-302.
    16. Velarde, Carlos & Robledo, Alberto, 2021. "Statistical mechanical model for growth and spread of contagions under gauged population confinement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    17. Almiala, Into & Aalto, Henrik & Kuikka, Vesa, 2023. "Influence spreading model for partial breakthrough effects on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    18. Xiao, Guanping & Zheng, Zheng & Wang, Haoqin, 2017. "Evolution of Linux operating system network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 249-258.
    19. Luis Lorenzo & Javier Arroyo, 2022. "Analysis of the cryptocurrency market using different prototype-based clustering techniques," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-46, December.
    20. I. Vieira & R. Cheng & P. Harper & V. Senna, 2010. "Small world network models of the dynamics of HIV infection," Annals of Operations Research, Springer, vol. 178(1), pages 173-200, July.

    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:468:y:2017:i:c:p:434-444. 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.