Quantifying the Complexity of Nodes in Higher-Order Networks Using the Infomap Algorithm

Accurately quantifying the complexity of nodes in a network is crucial for revealing their roles and network complexity, as well as predicting network emergent phenomena. In this paper, we propose three novel complexity metrics for nodes to reflect the extent to which they participate in organized, structured interactions in higher-order networks. Our higher-order network is built using the BuildHON+ model, where communities are detected using the Infomap algorithm. Since a physical node may contain one or more higher-order nodes in higher-order networks, it may simultaneously exist in one or more communities. The complexity of a physical node is defined by the number and size of the communities to which it belongs, as well as the number of higher-order nodes it contains within the same community. Empirical flow datasets are used to evaluate the effectiveness of the proposed metrics, and the results demonstrate their efficacy in characterizing node complexity in higher-order networks.

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Publication Details

Journal
Systems
Published
2024-09-03
DOI
https://doi.org/10.3390/systems12090347
Citations
2
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.56

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article

Quantifying the Complexity of Nodes in Higher-Order Networks Using the Infomap Algorithm

Yude Fu, Qizi Huangpeng, Caixia Yu, Xiang Li et al.
2 citations
Systems
Complex Network Analysis Techniques
0.56
article

Quantifying the Complexity of Nodes in Higher-Order Networks Using the Infomap Algorithm

Yude Fu, Qizi Huangpeng, Caixia Yu, Xiang Li, Jichao Li, Xiongyi Lu
article en
2 citations

Abstract

Accurately quantifying the complexity of nodes in a network is crucial for revealing their roles and network complexity, as well as predicting network emergent phenomena. In this paper, we propose three novel complexity metrics for nodes to reflect the extent to which they participate in organized, structured interactions in higher-order networks. Our higher-order network is built using the BuildHON+ model, where communities are detected using the Infomap algorithm. Since a physical node may contain one or more higher-order nodes in higher-order networks, it may simultaneously exist in one or more communities. The complexity of a physical node is defined by the number and size of the communities to which it belongs, as well as the number of higher-order nodes it contains within the same community. Empirical flow datasets are used to evaluate the effectiveness of the proposed metrics, and the results demonstrate their efficacy in characterizing node complexity in higher-order networks.

SystemsVol. 12(9)
Zhejiang Normal University (CN), National University of Defense Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 35%
Complex Network Analysis Techniques
0.56
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Quantifying the Complexity of Nodes in Higher-Order Networks Using the Infomap Algorithm — Yude Fu, Qizi Huangpeng, et al. · Systems (2024) | TGRS Research Map | TGRS