Misinformed by Visualization: What Do We Learn From Misinformative Visualizations?

dc.contributor.authorLo, Leo Yu-Hoen_US
dc.contributor.authorGupta, Ayushen_US
dc.contributor.authorShigyo, Kentoen_US
dc.contributor.authorWu, Aoyuen_US
dc.contributor.authorBertini, Enricoen_US
dc.contributor.authorQu, Huaminen_US
dc.contributor.editorBorgo, Ritaen_US
dc.contributor.editorMarai, G. Elisabetaen_US
dc.contributor.editorSchreck, Tobiasen_US
dc.date.accessioned2022-06-03T06:06:31Z
dc.date.available2022-06-03T06:06:31Z
dc.date.issued2022
dc.description.abstractData visualization is powerful in persuading an audience. However, when it is done poorly or maliciously, a visualization may become misleading or even deceiving. Visualizations give further strength to the dissemination of misinformation on the Internet. The visualization research community has long been aware of visualizations that misinform the audience, mostly associated with the terms ''lie'' and ''deceptive.'' Still, these discussions have focused only on a handful of cases. To better understand the landscape of misleading visualizations, we open-coded over one thousand real-world visualizations that have been reported as misleading. From these examples, we discovered 74 types of issues and formed a taxonomy of misleading elements in visualizations. We found four directions that the research community can follow to widen the discussion on misleading visualizations: (1) informal fallacies in visualizations, (2) exploiting conventions and data literacy, (3) deceptive tricks in uncommon charts, and (4) understanding the designers' dilemma. This work lays the groundwork for these research directions, especially in understanding, detecting, and preventing them.en_US
dc.description.number3
dc.description.sectionheadersGeneral Public
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14559
dc.identifier.issn1467-8659
dc.identifier.pages515-525
dc.identifier.pages11 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14559
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14559
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Human-centered computing --> Information visualization
dc.subjectHuman centered computing
dc.subjectInformation visualization
dc.titleMisinformed by Visualization: What Do We Learn From Misinformative Visualizations?en_US
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