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    The Turing Test for Graph Drawing Algorithms

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    2008.04869.pdf
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    Author
    Purchase, Helen C.
    Archambault, Daniel
    Kobourov, Stephen
    Nöllenburg, Martin
    Pupyrev, Sergey
    Wu, Hsiang-Yun
    Affiliation
    University of Arizona
    Issue Date
    2021-02-14
    Keywords
    Empirical studies
    Graph drawing algorithms
    Turing test
    
    Metadata
    Show full item record
    Publisher
    Springer Science and Business Media Deutschland GmbH
    Citation
    Purchase, H. C., Archambault, D., Kobourov, S., Nöllenburg, M., Pupyrev, S., & Wu, H. Y. (2020). The Turing Test for Graph Drawing Algorithms. International Symposium on Graph Drawing and Network Visualization: Graph Drawing and Network Visualization, 466-481.
    Rights
    ©Springer Nature Switzerland AG 2020.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Do algorithms for drawing graphs pass the Turing Test? That is, are their outputs indistinguishable from graphs drawn by humans? We address this question through a human-centred experiment, focusing on ‘small’ graphs, of a size for which it would be reasonable for someone to choose to draw the graph manually. Overall, we find that hand-drawn layouts can be distinguished from those generated by graph drawing algorithms, although this is not always the case for graphs drawn by force-directed or multi-dimensional scaling algorithms, making these good candidates for Turing Test success. We show that, in general, hand-drawn graphs are judged to be of higher quality than automatically generated ones, although this result varies with graph size and algorithm. © 2020, Springer Nature Switzerland AG.
    Note
    12 month embargo; first published online 14 February 2021
    ISSN
    0302-9743
    EISSN
    1611-3349
    DOI
    10.1007/978-3-030-68766-3_36
    Version
    Final accepted manuscript
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-030-68766-3_36
    Scopus Count
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    UA Faculty Publications

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