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Order structure analysis of node importance based on the temporal inter-layer neighborhood homogeneity rate of the dynamic network

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Abstract

The analysis of node order structure in dynamic temporal networks is significant for network propagation control. To further accurately characterize the inter-layer coupling relationship of dynamic temporal networks, this paper firstly defines the node neighborhood structure homogeneity rate and node neighborhood location heterogeneity rate based on the node neighborhood structure evolution feature information and node neighborhood location evolution feature information, and integrates the influence of the change in both neighborhood structure and neighborhood location on the node importance in the process of node temporal evolution. Secondly, a Supra-Adjacency Matrix based on Neighborhood Structure (NSAM) temporal network node importance order structure modeling method is proposed by combining the local structure and overall structure evolution information of nodes during the temporal evolution process. Finally, the node importance order structure of the dynamic temporal network is obtained by combining the eigenvector centrality to represent the node importance attribute value. Simulations show that compared with the classical hierarchical temporal network model, the NSAM model can improve the identification accuracy by 38.2% and 7.8%, respectively, and can identify the important nodes in the dynamic temporal network more effectively.

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Availability of data and materials

The data cannot be made publicly available upon publication because they contain sensitive personal information. The data that support the findings of this study are available upon reasonable request from the authors. No datasets were generated or analyzed during the current study.

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Funding

This research is supported by the Project supported by the National Natural Science Foundation of China (Grant No. 62072249), the Natural Science Foundation of Anhui Province, China (Grant No. 2108085MG236) and the Natural Science Foundation of the Higher Education Institutions of Anhui Province, China (Grant No. KJ2021A0385). The authors thank the reviewers and editors for their constructive comments on improving this paper.

Author information

Authors and Affiliations

  1. School of Management Science and Engineering, Anhui University of Technology, 1530 Maxiang Road, Maanshan, 243032, Anhui, China

    Zhiyu Lu, Gang Hu & Lemeng Wang

  2. Key Laboratory of Mulidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes, 1530 Maxiang Road, Maanshan, 243032, Anhui, China

    Gang Hu

Authors
  1. Zhiyu Lu
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Contributions

The authors’ contributions are summarized below. L.-Z.Y. and H.-G. were involved in conceptualization and writing original draft preparation; L.-Z.Y., H.-G. and W.-L.M. contributed to methodology; L.-Z.Y. were involved in data analysis and validation; L.-Z.Y., H.-G. and W.-L.M. were involved in writing review and editing; all authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Gang Hu.

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This study is only based on theoretical basic research. It is not involving humans.

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Lu, Z., Hu, G. & Wang, L. Order structure analysis of node importance based on the temporal inter-layer neighborhood homogeneity rate of the dynamic network. J Supercomput 80, 17314–17337 (2024). https://doi.org/10.1007/s11227-024-06135-4

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