Taking Word Clouds Apart: An Empirical Investigation of the Design Space for Keyword Summaries

Cristian Felix, Steven Franconeri, Enrico Bertini

    Research output: Contribution to journalArticlepeer-review

    Abstract

    In this paper we present a set of four user studies aimed at exploring the visual design space of what we call keyword summaries: lists of words with associated quantitative values used to help people derive an intuition of what information a given document collection (or part of it) may contain. We seek to systematically study how different visual representations may affect people's performance in extracting information out of keyword summaries. To this purpose, we first create a design space of possible visual representations and compare the possible solutions in this design space through a variety of representative tasks and performance metrics. Other researchers have, in the past, studied some aspects of effectiveness with word clouds, however, the existing literature is somewhat scattered and do not seem to address the problem in a sufficiently systematic and holistic manner. The results of our studies showed a strong dependency on the tasks users are performing. In this paper we present details of our methodology, the results, as well as, guidelines on how to design effective keyword summaries based in our discoveries.

    Original languageEnglish (US)
    Article number8017641
    Pages (from-to)657-666
    Number of pages10
    JournalIEEE Transactions on Visualization and Computer Graphics
    Volume24
    Issue number1
    DOIs
    StatePublished - Jan 2018

    Keywords

    • Keyword Summaries
    • Tag Clouds
    • Text Visualization
    • Word Clouds

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Computer Vision and Pattern Recognition
    • Computer Graphics and Computer-Aided Design

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