Understanding graph sampling algorithms for social network analysis

Tianyi Wang, Yang Chen, Zengbin Zhang, Tianyin Xu, Long Jin, Pan Hui, Beixing Deng, Xing Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Being able to keep the graph scale small while capturing the properties of the original social graph, graph sampling provides an efficient, yet inexpensive solution for social network analysis. The challenge is how to create a small, but representative sample out of the massive social graph with millions or even billions of nodes. Several sampling algorithms have been proposed in previous studies, but there lacks fair evaluation and comparison among them. In this paper, we analyze the state-of art graph sampling algorithms and evaluate their performance on some widely recognized graph properties on directed graphs using large-scale social network datasets. We evaluate not only the commonly used node degree distribution, but also clustering coefficient, which quantifies how well connected are the neighbors of a node in a graph. Through the comparison we have found that none of the algorithms is able to obtain satisfied sampling results in both of these properties, and the performance of each algorithm differs much in different kinds of datasets.

Original languageEnglish (US)
Title of host publicationProceedings - 31st International Conference on Distributed Computing Systems Workshops, ICDCSW 2011
Pages123-128
Number of pages6
DOIs
StatePublished - Sep 9 2011
Externally publishedYes
Event31st International Conference on Distributed Computing Systems Workshops, ICDCSW 2011 - Minneapolis, MN, United States
Duration: Jun 20 2011Jun 24 2011

Publication series

NameProceedings - International Conference on Distributed Computing Systems

Other

Other31st International Conference on Distributed Computing Systems Workshops, ICDCSW 2011
CountryUnited States
CityMinneapolis, MN
Period6/20/116/24/11

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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  • Cite this

    Wang, T., Chen, Y., Zhang, Z., Xu, T., Jin, L., Hui, P., Deng, B., & Li, X. (2011). Understanding graph sampling algorithms for social network analysis. In Proceedings - 31st International Conference on Distributed Computing Systems Workshops, ICDCSW 2011 (pp. 123-128). [5961350] (Proceedings - International Conference on Distributed Computing Systems). https://doi.org/10.1109/ICDCSW.2011.34