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Chin. Phys. B, 2022, Vol. 31(7): 070203    DOI: 10.1088/1674-1056/ac5985
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Effect of observation time on source identification of diffusion in complex networks

Chaoyi Shi(史朝义)1, Qi Zhang(张琦)2, and Tianguang Chu(楚天广)1,†
1 College of Engineering, Peking University, Beijing 100871, China;
2 School of Information Technology and Management, University of International Business and Economics, Beijing 100105, China
Abstract  This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infected-recovered diffusion process in a network with snapshot of partial nodes. We formulate the source identification problem as a maximum likelihood (ML) estimator and develop a statistical inference method based on Monte Carlo simulation (MCS) to estimate the source location and the initial time of diffusion. Experimental results in synthetic networks and real-world networks demonstrate evident impact of the observation time as well as the fraction of the observers on the concerned problem.
Keywords:  complex network      source identification      statistical inference      partial observation  
Received:  29 December 2021      Revised:  30 January 2022      Accepted manuscript online:  02 March 2022
PACS:  02.70.Uu (Applications of Monte Carlo methods)  
  87.23.Ge (Dynamics of social systems)  
  89.75.-k (Complex systems)  
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61673027 and 62106047), the Beijing Social Science Foundation (Grant No. 21GLC042), and the Humanity and Social Science Youth foundation of Ministry of Education, China (Grant No. 20YJCZH228).
Corresponding Authors:  Tianguang Chu     E-mail:

Cite this article: 

Chaoyi Shi(史朝义), Qi Zhang(张琦), and Tianguang Chu(楚天广) Effect of observation time on source identification of diffusion in complex networks 2022 Chin. Phys. B 31 070203

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