VisQAC: Visual Analytics for Online Q&A Communities

Jing Liang, Ruoyu Jia, Min Zhu, Henry B.L. Duh

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Online question and answer (Q&A) communities, which allow users to exchange knowledge by asking and answering questions, have become increasingly popular. As a result of user active participation, these communities store overwhelming volumes of information. However, existing related methods are unable to meet community operators' needs for analyzing multi-dimensional Q&A sequences and understanding user behavior. In this paper, collaborating with domain experts in online community, we present a system, VisQAC, which explores the patterns of Q&A sequence and user behavior. In the system, a novel visual design is proposed, which is combined with flexible mapping measures for analyzing critical characteristics of sequence data. Moreover, a timeline visualization method is designed to visualize data with categorical attributes and its correlation can be displayed flexibly by choosing time mode and time granularity. The usefulness and effectiveness of the system are demonstrated with several case studies of VisQAC with community operators based on the Zhihu dataset. Our evaluation shows that VisQAC is beneficial to the understanding of Q&A sequence and associated user behavior.

Original languageEnglish
Pages (from-to)305-317
Number of pages13
JournalJournal of Beijing Institute of Technology (English Edition)
Issue number2
Publication statusPublished - 1 Jun 2019
Externally publishedYes


  • Online Q&A community
  • Sequence data
  • User behavior
  • Visual analytics

ASJC Scopus subject areas

  • Engineering(all)


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