Group profiling for understanding social structures

Lei Tang, Wang Xufei Wang, Huan Liu

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


The prolific use of participatory Web and social networking sites is reshaping the ways in which people interact with one another. It has become a vital part of human social life in both the developed and developing world. People sharing certain similarities or affiliates tend to form communities within social media. At the same time, they participate in various online activities: content sharing, tagging, posting status updates, etc. These diverse activities leave behind traces of their social life, providing clues to understand changing social structures. A large body of existing work focuses on extracting cohesive groups based on network topology. But little attention is paid to understanding the changing social structures. In order to help explain the formation of a group, we explore different group-profiling strategies to construct descriptions of a group. This research can assist network navigation, visualization, and analysis, as well as monitoring and tracking the ebbs and tides of different groups in evolving networks. By exploiting information collected from real-world social media sites, extensive experiments are conducted to evaluate group-profiling results. The pros and cons of different group-profiling strategies are analyzed with concrete examples. We also show some potential applications based on group profiling. Interesting findings with discussions are reported.

Original languageEnglish (US)
Article number15
JournalACM Transactions on Intelligent Systems and Technology
Issue number1
StatePublished - Oct 1 2011


  • Community
  • Group formation
  • Group profiling
  • Social media
  • Social structure

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Artificial Intelligence


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