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A community scale test for node affiliation based on network sampling and wavelet analysis

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  • Wang, Tingting
  • Wang, Zhen

Abstract

This paper addresses the challenge of determining community scale to which network nodes belong and introduces an innovative hypothesis testing approach. It begins with a network sampling method that generates sequences of node dependency values, revealing community structure and scale in a waveform-like manner. Subsequently, the study employs wavelet analysis, a signal processing technique, to extract local signal periodicity information from these sequences. This information is then used to develop a test for assessing node membership in specific community scales. The proposed method is applied to both simulated and real-world social network data, with results from the simulated data demonstrating its effectiveness in evaluating node membership in particular community scales.

Suggested Citation

  • Wang, Tingting & Wang, Zhen, 2024. "A community scale test for node affiliation based on network sampling and wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    • Handle: RePEc:eee:phsmap:v:643:y:2024:i:c:s0378437124002875
    DOI: 10.1016/j.physa.2024.129778
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    References listed on IDEAS

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