Measuring and utilizing temporal network dissimilarity
Abstract Quantifying the structural and functional differences of temporal networks remains a fundamental and challenging problem in the era of big data. Traditional network comparison methods, originally developed for static networks, often fall short in capturing the intricate interplay between st...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-025-01940-6 |
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| _version_ | 1832585617347706880 |
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| author | Xiu-Xiu Zhan Chuang Liu Zhipeng Wang Huijuan Wang Petter Holme Zi-Ke Zhang |
| author_facet | Xiu-Xiu Zhan Chuang Liu Zhipeng Wang Huijuan Wang Petter Holme Zi-Ke Zhang |
| author_sort | Xiu-Xiu Zhan |
| collection | DOAJ |
| description | Abstract Quantifying the structural and functional differences of temporal networks remains a fundamental and challenging problem in the era of big data. Traditional network comparison methods, originally developed for static networks, often fall short in capturing the intricate interplay between structural configurations and dynamic temporal patterns inherent in complex systems. This work proposes a temporal dissimilarity measure for temporal network comparison based on the first arrival distance distribution and spectral entropy based Jensen-Shannon divergence. Experimental results on both synthetic and empirical temporal networks show that the proposed measure could discriminate diverse temporal networks with different structures by capturing various topological and temporal properties. Moreover, the proposed measure can discern the functional distinctions and is found effective applications in temporal network classification and spreadability discrimination. |
| format | Article |
| id | doaj-art-1c0dc1e4d0eb42189bd1bac8d90e6ca2 |
| institution | Kabale University |
| issn | 2399-3650 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Physics |
| spelling | doaj-art-1c0dc1e4d0eb42189bd1bac8d90e6ca22025-01-26T12:37:06ZengNature PortfolioCommunications Physics2399-36502025-01-01811910.1038/s42005-025-01940-6Measuring and utilizing temporal network dissimilarityXiu-Xiu Zhan0Chuang Liu1Zhipeng Wang2Huijuan Wang3Petter Holme4Zi-Ke Zhang5Research Center for Complexity Sciences, Hangzhou Normal UniversityResearch Center for Complexity Sciences, Hangzhou Normal UniversitySchool of Systems Science, Beijing Normal UniversityFaculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of TechnologyDepartment of Computer Science, Aalto UniversityCenter for Digital Communication Studies, Zhejiang UniversityAbstract Quantifying the structural and functional differences of temporal networks remains a fundamental and challenging problem in the era of big data. Traditional network comparison methods, originally developed for static networks, often fall short in capturing the intricate interplay between structural configurations and dynamic temporal patterns inherent in complex systems. This work proposes a temporal dissimilarity measure for temporal network comparison based on the first arrival distance distribution and spectral entropy based Jensen-Shannon divergence. Experimental results on both synthetic and empirical temporal networks show that the proposed measure could discriminate diverse temporal networks with different structures by capturing various topological and temporal properties. Moreover, the proposed measure can discern the functional distinctions and is found effective applications in temporal network classification and spreadability discrimination.https://doi.org/10.1038/s42005-025-01940-6 |
| spellingShingle | Xiu-Xiu Zhan Chuang Liu Zhipeng Wang Huijuan Wang Petter Holme Zi-Ke Zhang Measuring and utilizing temporal network dissimilarity Communications Physics |
| title | Measuring and utilizing temporal network dissimilarity |
| title_full | Measuring and utilizing temporal network dissimilarity |
| title_fullStr | Measuring and utilizing temporal network dissimilarity |
| title_full_unstemmed | Measuring and utilizing temporal network dissimilarity |
| title_short | Measuring and utilizing temporal network dissimilarity |
| title_sort | measuring and utilizing temporal network dissimilarity |
| url | https://doi.org/10.1038/s42005-025-01940-6 |
| work_keys_str_mv | AT xiuxiuzhan measuringandutilizingtemporalnetworkdissimilarity AT chuangliu measuringandutilizingtemporalnetworkdissimilarity AT zhipengwang measuringandutilizingtemporalnetworkdissimilarity AT huijuanwang measuringandutilizingtemporalnetworkdissimilarity AT petterholme measuringandutilizingtemporalnetworkdissimilarity AT zikezhang measuringandutilizingtemporalnetworkdissimilarity |