Encyclopedia of Social Network Analysis and Mining

2018 Edition
| Editors: Reda Alhajj, Jon Rokne

Evolving Social Graph Clustering

  • Athena Vakali
Reference work entry
DOI: https://doi.org/10.1007/978-1-4939-7131-2_47




Incremental adaptation-driven evolving clustering


Milestones’ detection-driven evolving clustering


Sequential mapping-driven evolving clustering


Temporal smoothing-driven evolving clustering


Social graphs In the current Web 2.0 or social Web era, users’ intensive engagement in social networking and content sharing applications results in the formation of a massive amount of new associations daily among the actors involved. The types of such associations vary, depending on the application at hand, and may correspond to either explicit or implicit relationships invoked by users’ actions.


Associations formed in the context of social networking applications are often multiway; i.e., they involve multiple entities (e.g., user A commenting on post P of user B) and are more precisely captured in a generalized graph structure (i.e., hypergraph) with its (hyper)edges connecting more than two nodes....
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Copyright information

© Springer Science+Business Media LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of InformaticsAristotle University of ThessalonikiThessalonikiGreece

Section editors and affiliations

  • Mick J Ridley
    • 1
  • Richard Chbeir
    • 2
  1. 1.University of BradfordBradfordUK
  2. 2.Laboratoire LIUPPAUniversity of Pau and Adour CountriesAngletFrance