Author
Purchase, Helen C.Archambault, Daniel
Kobourov, Stephen
Nöllenburg, Martin
Pupyrev, Sergey
Wu, Hsiang-Yun
Affiliation
University of ArizonaIssue Date
2021-02-14
Metadata
Show full item recordCitation
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 2021ISSN
0302-9743EISSN
1611-3349Version
Final accepted manuscriptae974a485f413a2113503eed53cd6c53
10.1007/978-3-030-68766-3_36