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Locating the source of spreading in temporal networks

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  • 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
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    References listed on IDEAS

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    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.
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    Cited by:

    1. 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.
    2. 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.
    3. 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).
    4. 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).
    5. Li, Huichun & Zhang, Xue & Zhao, Chengli, 2021. "Explaining social events through community evolution on temporal networks," Applied Mathematics and Computation, Elsevier, vol. 404(C).

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