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dc.contributor.authorPurchase, Helen C.
dc.contributor.authorArchambault, Daniel
dc.contributor.authorKobourov, Stephen
dc.contributor.authorNöllenburg, Martin
dc.contributor.authorPupyrev, Sergey
dc.contributor.authorWu, Hsiang-Yun
dc.date.accessioned2021-04-07T21:45:25Z
dc.date.available2021-04-07T21:45:25Z
dc.date.issued2021-02-14
dc.identifier.citationPurchase, 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.en_US
dc.identifier.issn0302-9743
dc.identifier.doi10.1007/978-3-030-68766-3_36
dc.identifier.urihttp://hdl.handle.net/10150/657639
dc.description.abstractDo 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.en_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.rights©Springer Nature Switzerland AG 2020.en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectEmpirical studiesen_US
dc.subjectGraph drawing algorithmsen_US
dc.subjectTuring testen_US
dc.titleThe Turing Test for Graph Drawing Algorithmsen_US
dc.typeArticleen_US
dc.identifier.eissn1611-3349
dc.contributor.departmentUniversity of Arizonaen_US
dc.description.note12 month embargo; first published online 14 February 2021en_US
dc.description.collectioninformationThis 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.en_US
dc.eprint.versionFinal accepted manuscripten_US
dc.source.booktitleLecture Notes in Computer Science
dc.source.booktitleGraph Drawing and Network Visualization
dc.source.beginpage466
dc.source.endpage481


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