Summarization of social activity over time: People, actions and concepts in dynamic networks

Yu Ru Lin, Hari Sundaram, Aisling Kelliher

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

Abstract

We present a framework for automatically summarizing social group activity over time. The problem is important in understanding large scale online social networks, which have diverse social interactions and exhibit temporal dynamics. In this work we construct summarization by extracting activity themes. We propose a novel unified temporal multi-graph framework for extracting activity themes over time. We use non-negative matrix factorization (NMF) approach to derive two interrelated latent spaces for users and concepts. Activity themes are extracted from the derived latent spaces to construct group activity summary. Experiments on real-world Flickr datasets demonstrate that our technique outperforms baseline algorithms such as LSI, and is additionally able to extract temporally representative activities to construct meaningful group activity summary.

Original languageEnglish (US)
Title of host publicationProceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08
Pages1379-1380
Number of pages2
DOIs
StatePublished - Dec 1 2008
Externally publishedYes
Event17th ACM Conference on Information and Knowledge Management, CIKM'08 - Napa Valley, CA, United States
Duration: Oct 26 2008Oct 30 2008

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other17th ACM Conference on Information and Knowledge Management, CIKM'08
Country/TerritoryUnited States
CityNapa Valley, CA
Period10/26/0810/30/08

Keywords

  • Community
  • Evolution
  • Nonnegative matrix factorization
  • Social activity
  • Social network analysis
  • Summarization

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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