Testing the Susceptibility of Users to Deceptive Data Visualizations When Paired with Explanatory Text

The Deceptive Potential of Common Design Tactics Used in Data Visualizations

“…This holds true across varying amounts of data shown in the graphs, as there were only two data points in the bar and bubble graphs, seven in the pie, and eleven in the line graph. These results confirm Pandey et al [5] and O'Brien & Lauer [3], while extending those studies to show deceptiveness in the new genres of a line graph with a truncated axis and a pie graph with a 3D bevel effect.…”

“…Our study showed that people are deceived by common deceptive techniques used in data visualizations, This finding extended research done by Panday et al [3] and O'Brien & Lauer [4] by studying additional graph types and deceptive tactics, including pie graphs constructed with spatial exaggeration and line graphs constructed with truncated axes. Our study also introduced insightful qualitative data that enabled us to better understand how people were reading graphs and, more importantly, how they were positioning themselves and their sense of agency as readers in relation to the various graphs they were studying.…”

“…Pandey et al was the first to empirically show that participants were more likely to be misled in their interpretations of data visualizations that employed deceptive tactics such as message reversal (e.g., an inverted axis) and message exaggeration (e.g., truncated y-axis) [5]. Following this, O'Brien and Lauer found that people's perception of information presented in deceptive data visualizations persisted even when the deceptive graphic was paired with a paragraph of accurate text [3]. Researchers are currently investigating strategies to alleviate the deceptive potential of the data visualizations, such as giving users the option of using tools to zoom in on areas of the data visualization [22], though these options have not been entirely successful and more research is needed to help fully understand the extent to which deceptive data visualizations can and do deceive people.…”

“…This study empirically explores the relationship between deceptive tactics paired with exaggerated titles, and builds on previous work that examined deceptive tactics paired with paragraphs of accurate text [3]. As little empirical research exists in this area of TPC [1], we relied on research that has been conducted in related fields like psychology, human-computer interaction, computer science, and user experience to contextualize how this research fits into the larger discussion of deceptive tactics and comprehension.…”

“…The deceptive potential of data visualizations has been discussed by practitioners and theorists [2][3][4][5], and they have made recommendations for how developers can avoid inadvertently deceiving those to whom they are communicating data [2,6,7]. Such recommendations include starting y-axes at zero, framing data broadly enough to accurately represent trends, avoiding 3-D effects that can misrepresent the size or angle of data points, and avoiding randomly spaced data points; though there is still some debate over whether these recommendations should be adhered to at all times, or whether there are instances in which they can be discarded depending on the focus of the data being communicated [8][9][10][11].…”