A time scale measurement method for dynamic temporal networks

Miaojingxin Wu, Shengwen Yang, Yanjun Ye and Hongyang Ji

Physica A: Statistical Mechanics and its Applications, 2025, vol. 657, issue C

Abstract: Selecting an appropriate time scale is paramount for analysing dynamic temporal networks. This paper presents a systematic and data-driven framework for selecting suitable time scales for analysing these networks. The concept of multi-scale entropy is initially introduced to describe the complexity and stochasticity of time series and to determine a suitable range of time scales. The optimal time scale is defined and calculated, and a comprehensive assessment is conducted regarding node characteristics, edge characteristics, and the overall structure. Finally, the effectiveness of the proposed approach is verified by identifying pivotal nodes and using Susceptible-Infected-Recovered (SIR) dynamics propagation modelling, utilising three genuine traffic datasets as case studies. In addition, results from the empirical study on the Email-Eu-core network indicate that the proposed approach applies to social networks. This method enhances the scientific rigour, efficiency and practicality of dynamic temporal network analysis while providing novel conceptual frameworks and analytical tools for the field.

Keywords: Dynamic temporal network; Time scale; Multi-scale entropy; Key node identification (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437124007520
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:657:y:2025:i:c:s0378437124007520

DOI: 10.1016/j.physa.2024.130243

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().