The Deceptive Potential of Common Design Tactics Used in Data Visualizations

Abstract

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.

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

“…Among many misleading tricks, truncated axis, inverted axis, area encoding, dual‐axis, and rainbow colors are the most commonly picked for the studies, usually by heuristics or from the authors' experiences [PRS * 15,Cai15,CH17,MK18,Sza18,MWN * 18, ZS19, HCS20, LO20]. The notorious inverted axis visualization titled “Gun deaths in Florida” has been frequently discussed.…”

“…Nowadays, we have a much larger data source on the Internet. Still, the discussions among the research community are still focused on a limited set of cases – most commonly, truncated axis, area encoding, and 3D charts [PRS * 15,Cai15,CH17,MK18,Sza18,MWN * 18, ZS19, HCS20, LO20]. We imagine that taking a broad look at theproblem will help further the discussion, and perhaps we may find commonalities in other cases that may lead to breakthroughs on these long‐discussed cases.…”

Misleading Beyond Visual Tricks: How People Actually Lie with Charts

“…The first influential works that discuss deceptive charts in general context, such as Darrell Huff's 1954 book How to Lie with Statistics [22] and Edward Tufte's 1983 book The Visual Display of Quantitative Information [68], set the tone for the research and commentary on misleading visualizations for years to come [4,9,32,33,49,65]. Tufte [68] introduces the notions of graphical integrity and lie factor, underscoring the importance of the size of the visual encoding matching the magnitude of the underlying value.…”