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Cross-layers cascade in multiplex networks

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Abstract

The study of information cascade in multiplex networks, where agents are connected by using multiple linking types, has received increasing attention. Compared with the cascade in simplex networks, a noticeable characteristic of the cascade in multiplex networks is that information may be spread between multiple layers. In this study, we focus on the cross-layers cascade, which helps clarify two opposing opinions about the information cascade in multiplex networks: multiplexity can speed up or slow down information cascade. The linear threshold model is generalized into multiplex networks as conjoint agents become active, if the influences of active neighbors in any layer reach a predefined threshold. The preconditions and reasons for the slow-down and speed-up phenomena are discussed using four representative case studies and theoretical analyses. Next, analytical results are validated by using extensive simulations in which the multiplex networks are generated by random, small-world and scale-free network models. It is found that the slow-down phenomenon emerges due to the obstruction of cross-layers cascade which connects the distributed shortest path in multiple layers and the inhibitory effect of negative influence. Conversely, extra short paths or rapid spreading in one additional layer can facilitate the cascade process in existing networks, respectively. Extensive simulations also show that multiplex networks consisting of different network models are more competent for the cascade process compared with multiplex networks generated by a single network model. In conclusion, the concept of cross-layers cascade may elucidate the additional study of information spreading in multiplex networks.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61170164, and No. 61472079), the Funds for Distinguished Young Scholars of the Natural Science Foundation of Jiangsu Province (No.BK2012020), the Program for Distinguished Talents of Six Domains in Jiangsu Province (No. 2011-DZ023), and the Scientific Research Foundation of Graduate School of Southeast University (No. YBJJ1449).

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Zhaofeng Li, Fuhan Yan & Yichuan Jiang

  2. School of Computer Science and Engineering, Southeast University, Nanjing, 211189, China

    Zhaofeng Li, Fuhan Yan & Yichuan Jiang

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  1. Zhaofeng Li
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  2. Fuhan Yan
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Correspondence to Yichuan Jiang.

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Portions of this work appeared as a full paper in AAMAS 2014.

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Li, Z., Yan, F. & Jiang, Y. Cross-layers cascade in multiplex networks. Auton Agent Multi-Agent Syst 29, 1186–1215 (2015). https://doi.org/10.1007/s10458-015-9305-5

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