The Curious Case of Combining Text and Visualization

dc.contributor.authorOttley, Alvittaen_US
dc.contributor.authorKaszowska, Aleksandraen_US
dc.contributor.authorCrouser, R. Jordanen_US
dc.contributor.authorPeck, Evan M.en_US
dc.contributor.editorJohansson, Jimmy and Sadlo, Filip and Marai, G. Elisabetaen_US
dc.date.accessioned2019-06-02T18:14:47Z
dc.date.available2019-06-02T18:14:47Z
dc.date.issued2019
dc.description.abstractVisualization research has made significant progress in demonstrating the value of graphical data representation. Even still, the value added by static visualization is disputed in some areas. When presenting Bayesian reasoning information, for example, some studies suggest that combining text and visualizations could have an interactive effect. In this paper, we use eye tracking to compare how people extract information from text and visualization. Using a Bayesian reasoning problem as a test bed, we provide evidence that visualization makes it easier to identify critical information, but that once identified as critical, information is more easily extracted from the text. These tendencies persist even when text and visualization are presented together, indicating that users do not integrate information well across the two representation types. We discuss these findings and argue that effective representations should consider the ease of both information identification and extraction.en_US
dc.description.sectionheadersText Visualization and Applications
dc.description.seriesinformationEuroVis 2019 - Short Papers
dc.identifier.doi10.2312/evs.20191181
dc.identifier.isbn978-3-03868-090-1
dc.identifier.pages121-125
dc.identifier.urihttps://doi.org/10.2312/evs.20191181
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evs20191181
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisualization
dc.titleThe Curious Case of Combining Text and Visualizationen_US
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