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A Task-Based Evaluation of Combined Set and Network Visualization

Rodgers, Peter, Stapleton, Gem, Alsallakh, Bilal, Micallef, Luana, Baker, Robert, Thompson, Simon (2016) A Task-Based Evaluation of Combined Set and Network Visualization. Information Sciences, 367–8 . pp. 58-79. ISSN 0020-0255. (doi:10.1016/j.ins.2016.05.045)

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Abstract

This paper addresses the problem of how best to visualize network data grouped into overlapping sets. We address it by evaluating various existing techniques alongside a new technique. Such data arise in many areas, including social network analysis, gene expression data, and crime analysis. We begin by investigating the strengths and weakness of four existing techniques, namely Bubble Sets, EulerView, KelpFusion, and LineSets, using principles from psychology and known layout guides. Using insights gained, we propose a new technique, SetNet, that may overcome limitations of earlier methods. We conducted a comparative crowdsourced user study to evaluate all five techniques based on tasks that require information from both the network and the sets. We established that EulerView and SetNet, both of which draw the sets first, yield significantly faster user responses than Bubble Sets, KelpFusion and LineSets, all of which draw the network first.

Item Type: Article
DOI/Identification number: 10.1016/j.ins.2016.05.045
Uncontrolled keywords: Set visualization, graph visualization, combined visualization,clustering, networks
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Peter Rodgers
Date Deposited: 01 Jun 2016 06:59 UTC
Last Modified: 29 May 2019 17:25 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/55733 (The current URI for this page, for reference purposes)
Rodgers, Peter: https://orcid.org/0000-0002-4100-3596
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