Statistical properties of community structure in large social and information networks

A large body of work has been devoted to identifying community structure in networks. A community is often though of as a set of nodes that has more connections between its members than to the remainder of the network. In this paper, we characterize as a function of size the statistical and structural properties of such sets of nodes. We define the network community profile plot, which characterizes the "best" possible community--according to the conductance measure--over a wide range of size scales, and we study over 70 large sparse real-world networks taken from a wide range of application domains. Our results suggest a significantly more refined picture of community structure in large real-world networks than has been appreciated previously. Our most striking finding is that in nearly every network dataset we examined, we observe tight but almost trivial communities at very small scales, and at larger size scales, the best possible communities gradually "blend in&quo...

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Michael W. Mahoney
• Keywords: Internet Technology, Large Real-world Networks, Network Community Structure, Sparse Real-world Networks, WWW 2008