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Contributions to Proceedings:

H. Purchase, D. Archambault, S.G. Kobourov, M. Nöllenburg, S. Pupyrev, H. Wu:
"The Turing Test for Graph Drawing Algorithms";
in: "Proceedings of the 28th International Symposium on Graph Drawing and Network Visualization (GD2020)", D. Archambault (ed.); IEEE C.P.S. Publishing Services, 2020, 1 - 16.



English abstract:
Do algorithms for drawing graphs pass the Turing Test? Thatis, are their outputs indistinguishable from graphs drawn by humans? Weaddress this question through a human-centred experiment, focusing on`smallī graphs, of a size for which it would be reasonable for someone tochoose to draw the graph manually. Overall, we find that hand-drawnlayouts can be distinguished from those generated by graph drawing al-gorithms, although this is not always the case for graphs drawn by force-directed or multi-dimensional scaling algorithms, making these good can-didates for Turing Test success. We show that, in general, hand-drawngraphs are judged to be of higher quality than automatically generatedones, although this result varies with graph size and algorithm.

Keywords:
Empirical studies, Graph Drawing Algorithms, Turing Test


Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_291448.pdf


Created from the Publication Database of the Vienna University of Technology.