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Multiple propagation paths enhance locating the source of diffusion in complex networks

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  • Gajewski, Ł.G.
  • Suchecki, K.
  • Hołyst, J.A.

Abstract

We investigate the problem of locating the source of diffusion in complex networks without complete knowledge of nodes’ states. Some currently known methods assume the information travels via a single, shortest path, which by assumption is the fastest way. We show that such a method leads to the overestimation of propagation time for synthetic and real networks, where multiple shortest paths as well as longer paths between vertices exist. We propose a new method of source estimation based on maximum likelihood principle, that takes into account existence multiple shortest paths. It shows up to 1.6 times higher accuracy in synthetic and real networks.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:519:y:2019:i:c:p:34-41
    DOI: 10.1016/j.physa.2018.12.012
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    References listed on IDEAS

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    1. Cristopher Moore & M. E. J. Newman, 2000. "Epidemics and Percolation in Small-World Networks," Working Papers 00-01-002, Santa Fe Institute.
    2. 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.
    3. Zhang, Xizhe & Zhang, Yubo & Lv, Tianyang & Yin, Ying, 2016. "Identification of efficient observers for locating spreading source in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 100-109.
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    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. Ma, Yinghong & Song, Le & Ji, Zhaoxun & Wang, Qian & Yu, Qinglin, 2020. "Scholar’s career switch adhesive with research topics: An evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    3. 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).

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