Node-centric detection of overlapping communities in social networks

Yehonatan Cohen, Danny Hendler, Amir Rubin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

We present NECTAR, a community detection algorithm that generalizes Louvain method's local search heuristic for overlapping community structures. NECTAR chooses dynamically which objective function to optimize based on the network on which it is invoked. Our experimental evaluation on both synthetic benchmark graphs and real-world networks, based on ground-truth communities, shows that NECTAR provides excellent results as compared with state of the art community detection algorithms.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
EditorsRavi Kumar, James Caverlee, Hanghang Tong
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1384-1385
Number of pages2
ISBN (Electronic)9781509028467
DOIs
StatePublished - 21 Nov 2016
Event2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States
Duration: 18 Aug 201621 Aug 2016

Conference

Conference2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Country/TerritoryUnited States
CitySan Francisco
Period18/08/1621/08/16

Keywords

  • Community detection
  • Louvain method
  • modularity
  • objective function
  • overlapping communities

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