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A spanning tree approach to social network sampling with degree constraints

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Abstract

Online social networks (OSNs) have become increasingly popular on the web in recent years. There are millions of users on these networks, and they generate a great deal of interaction among them. Network sampling is often used to study and measure OSNs, which produce a small, accessible network with a limited number of edges and nodes. In this paper, two algorithms are proposed to sample OSNs. The first algorithm finds several spanning trees with the highest number of nodes that satisfy a given degree constraint from randomly chosen root nodes; edges and nodes of computed spanning trees are ranked based on how often they appear in them. Finally, a fraction of the highly ranked nodes and edges are considered in the sampled network. Second, a partial spanning tree algorithm is proposed in place of a full spanning tree algorithm to improve the performance of the first algorithm. We conduct several experiments on well-known real networks to determine the performance of the proposed sampling algorithms. As a result of the experiments, the proposed algorithms outperformed some of the baseline and recently presented algorithms in terms of the Kolmogorov-Smirnov (KS) test, Skew Divergence (SD) distance, and Normalized Distance (ND).

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Data availability

Data is provided within the supplementary information files.

Notes

  1. A subgraph \(H\) is an induced subgraph of \(G\) if for any two vertices \(u v\) in \(H\), \(u\) and \(v\) are adjacent in \(H\) if and only if they are adjacent in G.

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Authors and Affiliations

  1. Department of Computer Engineering, University of Science and Culture, Tehran, Iran

    Alireza Rezvanian

  2. Computer Engineering Department, Faculty of Electrical and Computer Engineering, University of Kashan, Kashan, Iran

    S. Mehdi Vahidipour

  3. Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA

    Zeinab S. Jalali

Authors
  1. Alireza Rezvanian
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  2. S. Mehdi Vahidipour
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  3. Zeinab S. Jalali
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Contributions

AR and ZSJ proposed the original idea, developed the code, designed, performed the simulation experiments, wrote the main manuscript text, and prepared Figs. 1, 2, 3, 4, 5, 6, 7, 8, 9 and S.M.V. participated in the coordination of the study. All authors planned the work, analyzed the results, and reviewed the manuscript.

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Correspondence to Alireza Rezvanian.

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Rezvanian, A., Vahidipour, S.M. & Jalali, Z.S. A spanning tree approach to social network sampling with degree constraints. Soc. Netw. Anal. Min. 14, 101 (2024). https://doi.org/10.1007/s13278-024-01247-4

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