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.

Empirical studies, Graph Drawing Algorithms, Turing Test

Electronic version of the publication:

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