Statistical properties of sampled networks.

By S. Lee, Pan-Jun Kim, Hawoong Jeong. Physical review. E, Statistical, nonlinear, and soft matter physics, 2005

492 citations recorded by the source corpus.

We study the statistical properties of the sampled scale-free networks, deeply related to the proper identification of various real-world networks. We exploit three methods of sampling and investigate the topological properties such as degree and betweenness centrality distribution, average path length, assortativity, and clustering coefficient of sampled networks compared with those of original networks. It is found that the quantities related to those properties in sampled networks appear to be estimated quite differently for each sampling method. We explain why such a biased estimation of quantities would emerge from the sampling procedure and give appropriate criteria for each sampling method to prevent the quantities from being overestimated or underestimated.

Subfields: Geometry and Topology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/83cb0e20fae49e7995f5cb2d695904205d2f909c

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In Geometry and Topology

In Statistical and Nonlinear Physics

Citations in the corpus

Network science: A Review Focused on Tourism (2010, unknown): “The literature has produced much evidence on the issue of network sampling and the effect it might have on the topological characteristics of the whole network (Kossinets 2006; Lee et al. 2006).”
Comparing Brain Networks of Different Size and Connectivity Density Using Graph Theory (2010, background): “We note that down-sampling is indeed known to affect network characteristics [49–53].”
Measurement and analysis of online social networks (2007, methodology): “In social network graphs, collecting samples via the snowball method has been shown to underestimate the power-law coefficient, but to more closely match other metrics, including the overall clustering coefficient [29].”
Analysis of a large-scale weighted network of one-to-one human communication (2007, methodology): “This method of sampling is sometimes called snowball sampling [12].”
Walking in Facebook: A Case Study of Unbiased Sampling of OSNs (2010, background): “However, BFS leads to a bias towards high degree nodes [12], [13].”
Analysis of topological characteristics of huge online social networking services (2007, methodology): “Recently, extensive simulations are performed for several network sampling methods [10] and the eﬀect of missing data in social network analysis is studied [2].”