Proceedings: GI 2018

MultiCloud: Interactive Word Cloud Visualization for the Analysis of Multiple Texts

Markus John (University of Stuttgart), Eduard Marbach (University of Stuttgart), Steffen Lohmann (Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS), Florian Heimerl (University of Wisconsin-Madison, USA), Thomas Ertl (University of Stuttgart)

Proceedings of Graphics Interface 2018: Toronto, Ontario, 8-11 May 2018, 34 - 41

DOI 10.20380/GI2018.06

  • BibTex

    @inproceedings{John:2018:10.20380/GI2018.06,
    author = {John, Markus and Marbach, Eduard and Lohmann, Steffen and Heimerl, Florian and Ertl, Thomas},
    title = {MultiCloud: Interactive Word Cloud Visualization for the Analysis of Multiple Texts},
    booktitle = {Proceedings of Graphics Interface 2018},
    series = {GI 2018},
    year = {2018},
    isbn = {978-0-9947868-3-8},
    location = {Toronto, Ontario},
    pages = {34 -- 41},
    numpages = {8},
    doi = {10.20380/GI2018.06},
    publisher = {Canadian Human-Computer Communications Society / Soci{\'e}t{\'e} canadienne du dialogue humain-machine},
    keywords = {Visual text analysis, document analysis, word cloud},
    }

Abstract

Word Clouds have gained an impressive momentum for summarizing text documents in the last years. They visually communicate in a clear and descriptive way the most frequent words of a text. However, there are only very few word cloud visualizations that support a contrastive analysis of multiple documents. The available approaches provide comparable overviews of the documents, but have shortcomings regarding the layout, readability, and use of white space. To tackle these challenges, we propose MultiCloud, an approach to visualize multiple documents within a single word cloud in a comprehensible and visually appealing way. MultiCloud comprises several parameters and visual representations that enable users to alter the word cloud visualization in different aspects. Users can set parameters to optimize the usage of available space to get a visual representation that provides an easy visual association of words with the different documents. We evaluated MultiCloud with visualization researchers and a group of domain experts comprising five humanities scholars.