CUT: Community update and tracking in dynamic social networks

Hao Shang Ma, Jen Wei Huang

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

9 Citations (Scopus)

Abstract

Social network exhibits a special property: community structure. The community detection on a social network is like clustering on a graph, but the nodes in social network has unique name and the edges has some special properties like friendship, common interest. There have been many clustering methods can be used to detect the community structure on a static network. But in real-world, the social networks are usually dynamic, and the community structures always change over time. We propose Community Update and Tracking algorithm, CUT, to efficiently update and track the community structure algorithm in dynamic social networks. When the social network has some variations in different timestamps, we track the seeds of community and update the community structure instead of recalculating all nodes and edges in the network. The seeds of community is the base of community, we find some nodes which connected together tightly, and these nodes probably become communities. Therefore, our approach can quickly and efficiently update the community structure.

Original languageEnglish
Title of host publicationProceedings of the 7th Workshop on Social Network Mining and Analysis, SNA-KDD 2013
PublisherAssociation for Computing Machinery
ISBN (Print)9781450323307
DOIs
Publication statusPublished - 2013 Jan 1
Event7th Workshop on Social Network Mining and Analysis, SNA-KDD 2013 - Chicago, IL, United States
Duration: 2013 Aug 112013 Aug 14

Publication series

NameProceedings of the 7th Workshop on Social Network Mining and Analysis, SNA-KDD 2013

Other

Other7th Workshop on Social Network Mining and Analysis, SNA-KDD 2013
CountryUnited States
CityChicago, IL
Period13-08-1113-08-14

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'CUT: Community update and tracking in dynamic social networks'. Together they form a unique fingerprint.

Cite this