Sampling from Complex Networks with high Community Structures

TitleSampling from Complex Networks with high Community Structures
Publication TypeJournal Article
Year of Publication2012
AuthorsSalehi, M., H. R. Rabiee, and A. Rajabi
JournalChaos: An Interdisciplinary Journal of Nonlinear Science
Start Page023126
Date Published05/2012
KeywordsCommunity, Complex Network, Link-tracing, pagerank, Sampling, Social Network
AbstractIn this paper, we propose a novel link-tracing sampling algorithm, based on the concepts from PageRank vectors, to sample from networks with high community structures. Our method has two phases; (1) Sampling the closest nodes to the initial nodes by approximating personalized PageRank vectors, and (2) Jumping to a new community by using PageRank vectors and unknown neighbors. Empirical studies on several synthetic and real-world networks show that the proposed method improves the performance of network sampling compared to the popular link-based sampling methods in terms of accuracy and visited communities.
DOI<a href=";amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;a
Original PublicationAmerican Institute of Physics