Information Visualization Evaluation Using Crowdsourcing

dc.contributor.authorBorgo, Ritaen_US
dc.contributor.authorMicallef, Luanaen_US
dc.contributor.authorBach, Benjaminen_US
dc.contributor.authorMcGee, Fintanen_US
dc.contributor.authorLee, Bongshinen_US
dc.contributor.editorRobert S. Laramee and G. Elisabeta Marai and Michael Sedlmairen_US
dc.date.accessioned2018-06-02T17:51:58Z
dc.date.available2018-06-02T17:51:58Z
dc.date.issued2018
dc.description.abstractVisualization researchers have been increasingly leveraging crowdsourcing approaches to overcome a number of limitations of controlled laboratory experiments, including small participant sample sizes and narrow demographic backgrounds of study participants. However, as a community, we have little understanding on when, where, and how researchers use crowdsourcing approaches for visualization research. In this paper, we review the use of crowdsourcing for evaluation in visualization research. We analyzed 190 crowdsourcing experiments, reported in 82 papers that were published in major visualization conferences and journals between 2006 and 2017. We tagged each experiment along 36 dimensions that we identified for crowdsourcing experiments.We grouped our dimensions into six important aspects: study design & procedure, task type, participants, measures & metrics, quality assurance, and reproducibility. We report on the main findings of our review and discuss challenges and opportunities for improvements in conducting crowdsourcing studies for visualization research.en_US
dc.description.documenttypestar
dc.description.number3
dc.description.sectionheadersHuman Factors and Evaluation
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume37
dc.identifier.doi10.1111/cgf.13444
dc.identifier.issn1467-8659
dc.identifier.pages573-595
dc.identifier.urihttps://doi.org/10.1111/cgf.13444
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13444
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.3 [Computer Graphics]
dc.subjectPicture/Image Generation
dc.subjectLine and curve generation
dc.titleInformation Visualization Evaluation Using Crowdsourcingen_US
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