title: Sampling from complex networks with high community structures.
abstract: In 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.
authors: Digital Media Lab, Department of Computer Engineering, AICTC Research Center, Sharif University of Technology, Tehran, Iran. mostafa_salehi@ce.sharif.edu
authors: Mostafa
authors: M
authors: Salehi
authors: Hamid R
authors: HR
authors: Rabiee
authors: Arezo
authors: A
authors: Rajabi