The Small Community Phenomenon in Networks: Models, Algorithms and Applications

  • Pan Peng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7287)


We survey a recent new line of research on the small community phenomenon in networks, which characterizes the intuition and observation that in a broad class of networks, a significant fraction of nodes belong to some small communities. We propose the formal definition of this phenomenon as well as the definition of communities, based on which we are able to both study the community structure of network models, i.e., whether a model exhibits the small community phenomenon or not, and design new models that embrace this phenomenon in a natural way while preserving some other typical network properties such as the small diameter and the power law degree distribution. We also introduce the corresponding community detection algorithms, which not only are used to identify true communities and confirm the existence of the small community phenomenon in real networks but also have found other applications, e.g., the classification of networks and core extraction of networks.


Small Community Real Network Community Detection Preferential Attachment Collaboration Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Pan Peng
    • 1
    • 2
  1. 1.State Key Laboratory of Computer Science, Institute of SoftwareChinese Academy of SciencesChina
  2. 2.School of Information Science and EngineeringGraduate University of China Academy of SciencesBeijingChina

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