Community evolution in dynamic multi-mode networks

Lei Tang, Huan Liu, Jianping Zhang, Zohreh Nazeri

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

168 Citations (Scopus)

Abstract

A multi-mode network typically consists of multiple heterogeneous social actors among which various types of interactions could occur. Identifying communities in a multi-mode network can help understand the structural properties of the network, address the data shortage and unbalanced problems, and assist tasks like targeted marketing and finding influential actors within or between groups. In general, a network and the membership of groups often evolve gradually. In a dynamic multi-mode network, both actor membership and interactions can evolve, which poses a challenging problem of identifying community evolution. In this work, we try to address this issue by employing the temporal information to analyze a multi-mode network. A spectral framework and its scalability issue are carefully studied. Experiments on both synthetic data and real-world large scale networks demonstrate the efficacy of our algorithm and suggest its generality in solving problems with complex relationships.

Original languageEnglish (US)
Title of host publicationProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Pages677-685
Number of pages9
DOIs
StatePublished - 2008
Event14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008 - Las Vegas, NV, United States
Duration: Aug 24 2008Aug 27 2008

Other

Other14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008
CountryUnited States
CityLas Vegas, NV
Period8/24/088/27/08

Fingerprint

Scalability
Marketing
Structural properties
Experiments

Keywords

  • Community evolution
  • Dynamic heterogeneous network
  • Dynamic network analysis
  • Evolution
  • Multi-mode networks

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Tang, L., Liu, H., Zhang, J., & Nazeri, Z. (2008). Community evolution in dynamic multi-mode networks. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 677-685) https://doi.org/10.1145/1401890.1401972

Community evolution in dynamic multi-mode networks. / Tang, Lei; Liu, Huan; Zhang, Jianping; Nazeri, Zohreh.

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2008. p. 677-685.

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

Tang, L, Liu, H, Zhang, J & Nazeri, Z 2008, Community evolution in dynamic multi-mode networks. in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 677-685, 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008, Las Vegas, NV, United States, 8/24/08. https://doi.org/10.1145/1401890.1401972
Tang L, Liu H, Zhang J, Nazeri Z. Community evolution in dynamic multi-mode networks. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2008. p. 677-685 https://doi.org/10.1145/1401890.1401972
Tang, Lei ; Liu, Huan ; Zhang, Jianping ; Nazeri, Zohreh. / Community evolution in dynamic multi-mode networks. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2008. pp. 677-685
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