Research Output
Large-scale Argument Visualization (LSAV)
  Arguments are structures of premises and conclusions that underpin rational reasoning processes. Within complex knowledge domains, especially if they are contentious, argument structures can become large and complex. Visualization tools have been developed that support argument analysts and help them to work with arguments. Until recently, arguments were manually analysed from natural language text, or constructed from scratch, but new communication modes mean that increasing amounts of debate and the arguments therein can be captured digitally. Furthermore, new tools and techniques for argument mining are beginning to automate the process of extracting argument structure from natural language; leading to much larger argument datasets that present problems for the current generation of argument visualisation tools. Additionally, individual argument analysts have different foci which can lead to increased complexity within datasets, and additional facets that argument visu- alisations should account for but do not. We propose a tool for interacting with argument corpora that enable users to explore and understand the reasoning structure of large-scale arguments. The tool will support a range of interactivity techniques and will help users to explore and analyse large-scale arguments, to more rapidly comprehend complex new problem domains.

  • Date:

    06 June 2016

  • Publication Status:


  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    006.3 Artificial intelligence


Khartabil, D., Wells, S., & Kennedy, J. (2016). Large-scale Argument Visualization (LSAV). In Eurographics Conference on Visualization (EuroVis), Posters Track (2016)



Visualisation tools, argument datasets, reasoning structure,

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