Baseline Exposure to Common Data Visualization Types Among the U.S. Adult Population
Authors
Kiegan Rice (NORC at the University of Chicago), Nola du Toit (Research to Reach), Quentin Brummet (NORC at the University of Chicago), Heike Hofmann (University of Nebraska-Lincoln)
Presentation
- Session
- Kids these days don't learn anything anymore, let's fix that!
- Time
- Thursday, Nov 12, 15:36 – 15:48 (US/Eastern) · session 15:00 – 16:30
- Location
- Hall America north
Links
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Keywords
General Public, Science Communication, Visualization Literacy, Human-Subjects Quantitative Studies
Abstract
Data visualizations are a primary means of communicating statistical information to the public. Their expanding use across news media, public health, education, and government reporting places greater importance on audiences' ability to recognize and interpret them. While a significant body of prior research has established frameworks for the measurement of graph and visualization literacy, far less is known about everyday exposure to different kinds of charts and graphs among the general adult population. This gap limits our ability to meaningfully interpret differences in graph literacy, focus efforts on improving that literacy, and design visualizations that align with audience ability. Establishing population level estimates of exposure to data visualizations is therefore essential for improving visual communication and reducing misinterpretation of quantitative information. To address this gap, we surveyed a nationally representative sample of 1,168 U.S. adults via NORC's AmeriSpeak panel about their exposure to sixteen different common data visualization types. The resulting survey responses demonstrate pronounced differences in baseline exposure to data visualizations across chart types and demographic groups. While widely used formats such as bar, pie, line, and grouped bar charts are highly recognizable to the vast majority of U.S. adults, many other practitioner-favored chart types remain unfamiliar to substantial portions of the adult population. Exposure also differs significantly by age and education, with higher educational attainment linked to greater exposure and older adults reporting lower exposure overall. Our findings provide essential population level context on visualization literacy and underscore the importance of aligning data visualization design with audience exposure and experience.
For Practitioners
Data journalists, visualization literacy researchers, social science researchers, science educators, and others who present research findings to a broad audience would be interested in reading this paper. Practitioners can apply our findings on exposure to common data visualization types to inform their design choices for creating data visualizations and disseminating quantitative data, particularly when trying to reach a broad audience with varied technical backgrounds.