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International Conference on Cloud Computing and Security

ICCCS 2018: Cloud Computing and Security pp 369–383Cite as

Identifying Influential Spreaders by Temporal Efficiency Centrality in Temporal Network

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11067))

Abstract

Identifying influential spreaders is an important issue for capturing the dynamics of information diffusion in temporal networks. Most of the identification of influential spreaders in previous researches were focused on analysing static networks, rarely highlighted on dynamics. However, those measures which are proposed for static topologies only, unable to faithfully capture the effect of temporal variations on the importance of nodes. In this paper, a shortest temporal path algorithm is proposed for calculating the minimum time that information interaction between nodes. This algorithm can effectively find out the shortest temporal path when considering the network integrity. On the basis of this, the temporal efficiency centrality (TEC) algorithm in temporal networks is proposed, which identify influential nodes by removing each node and taking the variation of the whole network into consideration at the same time. To evaluate the effectiveness of this algorithm, we conduct the experiment on four real-world temporal networks for Susceptible-Infected-Recovered (SIR) model. By employing the imprecision and the Kendall’s au coefficient, The results show that this algorithm can effectively evaluate the importance of nodes in temporal networks.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (No. 61571143, No. 61261017and No. 61561014); Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (No. CRKL150112); Guangxi Cooperative Innovation Center of cloud computing and Big Data (No. YD1716); Guangxi Colleges and Universities Key Laboratory of cloud computing and complex systems; Guangxi Key Laboratory of Cryptography and Information Security (No. GCIS201613, No. GCIS201612).

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Authors and Affiliations

  1. Key Laboratory of Cognitive Radio and Information Processing, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, China

    Kai Xue & Junyi Wang

  2. Guangxi Key Laboratory of Cryptography and Information Security, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, China

    Kai Xue & Junyi Wang

Authors
  1. Kai Xue
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  2. Junyi Wang
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Correspondence to Kai Xue .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Xue, K., Wang, J. (2018). Identifying Influential Spreaders by Temporal Efficiency Centrality in Temporal Network. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11067. Springer, Cham. https://doi.org/10.1007/978-3-030-00018-9_33

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  • DOI: https://doi.org/10.1007/978-3-030-00018-9_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00017-2

  • Online ISBN: 978-3-030-00018-9

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