Abstract

Networks are a useful paradigm for representing various social, biological, and technological systems. Modeling the structure and formation of networks is made more difficult when the nodes in the network and the topology of the network change over time. The growth of the internet and social media, in particular, has provided researchers with huge amounts of data that make such studies both feasible and highly desirable.
A standard approach to network modeling assumes a generative model for links based on node attributes. That is, the nodes or objects modeled are assumed to have some (possibly latent) attributes, eg, group membership, and these latent properties determine the formation of links between nodes. A version of this approach which has achieved great success is the mixed membership stochastic blockmodel (MMSB)(Airoldi et al., 2008). MMSBs recognize that nodes often have multiple attributes …

Date

November 6, 2014

Authors

Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan

Book

Handbook of mixed membership models and their applications

Pages

527-545