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A time scale measurement method for dynamic temporal networks

Author

Listed:
  • Wu, Miaojingxin
  • Yang, Shengwen
  • Ye, Yanjun
  • Ji, Hongyang

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.

Suggested Citation

  • Wu, Miaojingxin & Yang, Shengwen & Ye, Yanjun & Ji, Hongyang, 2025. "A time scale measurement method for dynamic temporal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 657(C).
    • Handle: RePEc:eee:phsmap:v:657:y:2025:i:c:s0378437124007520
    DOI: 10.1016/j.physa.2024.130243
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