The deceptive potential of common design tactics used in data visualizations

Visualizations effectively communicate data about important political, social, environmental, and health topics to a wide range of audiences; however, longstanding trust of graphs as conveyors of factual data makes them an easy means for spreading misinformation. Scholars in technical and professional communication have not yet conducted needed empirical research into people's perception and comprehension of data visualizations, especially when part of larger information texts [1]. Our study investigated the extent to which people exaggerated the differences between data points when reading graphs about non-controversial topics that used deceptive techniques and/or exaggerated titles. Participants (n=329) were randomly assigned to view one of four treatments for four different graph types (bar, line, pie, and bubble) and then asked to answer a question about each graph. Results show that deceptive techniques used in the graphs (including truncated axes, 3-D exaggeration, and arbitrary sizing), caused participants to misinterpret information in the deceptive vs. control visualizations for all of the graphs regardless of graph type, previous visualization coursework or comfort level with reading graphs. Results also showed that the presence of exaggerated vs. control titles that accompanied each graph did not significantly influence the extent of the misinterpretation. We will discuss the implication of these findings for technical communication as well as avenues of future research already underway that investigate these topics further.