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Accurate Moving Distance Estimation via Multi-modal Fusion from IMU Sensors and WiFi Signal Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Identifying Influential Spreaders by Temporal Efficiency Centrality in Temporal Network

Authors : Kai Xue, Junyi Wang

Published in: Cloud Computing and Security

Publisher: Springer International Publishing

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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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Metadata
Title
Identifying Influential Spreaders by Temporal Efficiency Centrality in Temporal Network
Authors
Kai Xue
Junyi Wang
Copyright Year
2018
Book
Cloud Computing and Security

Print ISBN: 978-3-030-00017-2

Electronic ISBN: 978-3-030-00018-9

Copyright Year: 2018

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

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