Gender classification for web forums

Yulei Zhang, Yan Dang, Hsinchun Chen

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


More and more women are participating in and exchanging opinions through community-based online social media. Questions concerning gender differences in the new media have been raised. This paper proposes a feature-based text classification framework to examine online gender differences between Web forum posters by analyzing writing styles and topics of interest. Our experiment on an Islamic women's political forum shows that feature sets containing both content-free and content-specific features perform significantly better than those consisting of only content-free features, feature selection can improve the classification results significantly, and female and male participants have significantly different topics of interest.

Original languageEnglish (US)
Article number5723017
Pages (from-to)668-677
Number of pages10
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
Issue number4
StatePublished - Jul 2011


  • Gender classification
  • online gender differences

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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