Literature DB >> 28866580

Data Through Others' Eyes: The Impact of Visualizing Others' Expectations on Visualization Interpretation.

Yea-Seul Kim, Katharina Reinecke, Jessica Hullman.   

Abstract

In addition to visualizing input data, interactive visualizations have the potential to be social artifacts that reveal other people's perspectives on the data. However, how such social information embedded in a visualization impacts a viewer's interpretation of the data remains unknown. Inspired by recent interactive visualizations that display people's expectations of data against the data, we conducted a controlled experiment to evaluate the effect of showing social information in the form of other people's expectations on people's ability to recall the data, the degree to which they adjust their expectations to align with the data, and their trust in the accuracy of the data. We found that social information that exhibits a high degree of consensus lead participants to recall the data more accurately relative to participants who were exposed to the data alone. Additionally, participants trusted the accuracy of the data less and were more likely to maintain their initial expectations when other people's expectations aligned with their own initial expectations but not with the data. We conclude by characterizing the design space for visualizing others' expectations alongside data.

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Year:  2017        PMID: 28866580     DOI: 10.1109/TVCG.2017.2745240

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  3 in total

1.  Two graphs walk into a bar: Readout-based measurement reveals the Bar-Tip Limit error, a common, categorical misinterpretation of mean bar graphs.

Authors:  Sarah H Kerns; Jeremy B Wilmer
Journal:  J Vis       Date:  2021-11-01       Impact factor: 2.240

2.  Fostering compliance with physical distancing by interactive feedback in the context of the COVID-19 pandemic: A web-based randomized controlled trial.

Authors:  Tim Kaiser; Inga Mögling; Matthias Feldmann; Alfons Hamm; Eva-Lotta Brakemeier
Journal:  Internet Interv       Date:  2022-05-12

3.  A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare.

Authors:  Andrea Vázquez-Ingelmo; Alicia García-Holgado; Francisco José García-Peñalvo; Roberto Therón
Journal:  Sensors (Basel)       Date:  2020-07-22       Impact factor: 3.576

  3 in total

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