Sampling in online social networks

Sang Wook Kim, Seok Ho Yoon, Ki Nam Kim, Sunju Park

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

2 Citations (Scopus)

Abstract

In this paper, we propose a new graph sampling method for online social networks that achieves the following. First, a sample graph should reflect the ratio between the number of nodes and the number of edges of the original graph. Second, a sample graph should reflect the topology of the original graph. Third, sample graphs should be consistent with each other when they are sampled from the same original graph. The proposed method employs two techniques: hierarchical community extraction and densification power law. The proposed method partitions the original graph into a set of communities to preserve the topology of the original graph. It also uses the densification power law which captures the ratio between the number of nodes and the number of edges in online social networks. In experiments, we use several real-world online social networks, create sample graphs using the existing methods and ours, and analyze the differences between the sample graph by each sampling method and the original graph.

Original languageEnglish
Title of host publicationProceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014
PublisherAssociation for Computing Machinery
Pages845-849
Number of pages5
ISBN (Print)9781450324694
DOIs
Publication statusPublished - 2014 Jan 1
Event29th Annual ACM Symposium on Applied Computing, SAC 2014 - Gyeongju, Korea, Republic of
Duration: 2014 Mar 242014 Mar 28

Other

Other29th Annual ACM Symposium on Applied Computing, SAC 2014
CountryKorea, Republic of
CityGyeongju
Period14/3/2414/3/28

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All Science Journal Classification (ASJC) codes

  • Software

Cite this

Kim, S. W., Yoon, S. H., Kim, K. N., & Park, S. (2014). Sampling in online social networks. In Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014 (pp. 845-849). Association for Computing Machinery. https://doi.org/10.1145/2554850.2554907