The big friendly giant: the giant component in clustered random graphs

Yakir Berchenko, Yael Artzy-Randrup, Mina Teicher, Lewi Stone

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Network theory is a powerful tool for describing and modeling complex systems having applications in widelydiffering areas including epidemiology [16], neuroscience [34], ecology [20] and the Internet [26]. In its beginning, one often compared an empirically given network, whose nodes are the elements of the system and whose edges represent their interactions, with an ensemble having the same number of nodes and edges, the most popular example being the random graphs introduced by Erdos and Renyi [11]. As the field matured, it became clear that the naive model above needed to be refined, due to the observation that real-world networks often differ significantly from the Erdos–Renyi random graphs in having a highly heterogenous non-Poisson degree distribution [5, 15] and in possessing a high level of clustering [33]. Methods for generating random networks with arbitrary degree distributions and for calculating their statistical properties are now well understood.

Original languageEnglish
Title of host publicationModeling and Simulation in Science, Engineering and Technology
PublisherSpringer Basel
Number of pages16
StatePublished - 1 Jan 2009
Externally publishedYes

Publication series

NameModeling and Simulation in Science, Engineering and Technology
ISSN (Print)2164-3679
ISSN (Electronic)2164-3725

ASJC Scopus subject areas

  • Modeling and Simulation
  • General Engineering
  • Fluid Flow and Transfer Processes
  • Computational Mathematics


Dive into the research topics of 'The big friendly giant: the giant component in clustered random graphs'. Together they form a unique fingerprint.

Cite this