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The Impact of Visual Aesthetics on the Utility, Affordance, and Readability of Network Graphs

Dudas, Patrick M (2016) The Impact of Visual Aesthetics on the Utility, Affordance, and Readability of Network Graphs. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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The readability of networks – how different visual design elements affect the understanding of network data – has been central in network visualization research. However, existing studies have mainly focused on readability induced by topological mapping (based on different layouts) and overlooked the effect of visual aesthetics. Proposed is a novel experimental framework to study how different network aesthetic choices affect users' abilities of understanding the network structures. The visual aesthetics are grouped in two forms: 1) visual encoding (where the aesthetic mapping depends on the underlying network data) and 2) visual styling (where the aesthetics are applied independent of underlying data). Users are given a simple task – identifying most connected nodes in a network – in a hybrid experimental setting where the visual aesthetic choices are tested in a within-subject manner while the network topologies are tested in a between-subject manner based on a randomized blocking design. This novel experimental design ensures an efficient decoupling of the influence of network topology on readability tests. The utility of different visual aesthetics is measured comprehensively based on task performance (accuracy and time), eye-tracking data, and user feedback (perceived affordance). The results show differential readability effects among choices of visual aesthetics. Particularly, node based visual encoding significantly enhances network readability; specifically, glyphs allow participants to create more robust strategies in their utilization. The study contributes to both the understanding of the role of visual aesthetics in network visualization design and the experimental design for testing the network readability.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Dudas, Patrick Mpmd18@pitt.eduPMD18
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorHirtle, Stephen C.hirtle@pitt.eduHIRTLE
Committee MemberLewis, Michaelml@sis.pitt.eduCMLEWIS
Committee MemberLin, Yu-Ruyurulin@pitt.eduYURULIN
Committee MemberEverton,
Date: 13 January 2016
Date Type: Publication
Defense Date: 14 August 2015
Approval Date: 13 January 2016
Submission Date: 6 December 2015
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 171
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Eye-tracking; network graphs; visual encoding; user-behavior
Date Deposited: 13 Jan 2016 16:13
Last Modified: 15 Nov 2016 14:31


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