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Identifying similar networks using structural hierarchy

Author

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  • Saxena, Rakhi
  • Kaur, Sharanjit
  • Bhatnagar, Vasudha

Abstract

Comparing structural similarities among complex networks is an important task in several scientific and social science applications. Existing techniques for quantifying network similarity range from network-centric methods that consider global network topology to node-centric methods that consider local node-level sub-structures.

Suggested Citation

  • Saxena, Rakhi & Kaur, Sharanjit & Bhatnagar, Vasudha, 2019. "Identifying similar networks using structural hierarchy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    • Handle: RePEc:eee:phsmap:v:536:y:2019:i:c:s0378437119306399
    DOI: 10.1016/j.physa.2019.04.265
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    References listed on IDEAS

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    1. Vladimir Batagelj & Matjaž Zaveršnik, 2011. "Fast algorithms for determining (generalized) core groups in social networks," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(2), pages 129-145, July.
    2. Traud, Amanda L. & Mucha, Peter J. & Porter, Mason A., 2012. "Social structure of Facebook networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4165-4180.
    3. Shi, Xiaolin & Adamic, Lada A. & Strauss, Martin J., 2007. "Networks of strong ties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 33-47.
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