What Eye Tracking Can Show Us About How People Are Influenced by Deceptive Tactics in Line Graphs.

Background: Graphs, especially those that are generated automatically, are often subject to mistakes in their processing, framing, and construction, sending unintended messages that neither the viewer nor the author may realize. This article analyzes the eye-tracking data of 57 participants to extend the results of a previous study that investigated how people are deceived by common mistakes and deceptive tactics in data visualizations and titles. Literature review: Previous research has suggested that viewers are susceptible to deception by misleading titles or graph presentations, and that such information can influence how they interpret graphs. Previous eye-tracking research has only measured viewing patterns of nondeceptive graphs. Research questions: 1. How much attention do participants give to various areas of a graph when not given any instruction on what to look for, nor what they might be asked about? 2. Are there differences in how participants view and interpret deceptive versus control graphs about noncontroversial topics? 3. Are there differences in how participants view and interpret graphs about noncontroversial topics paired with control or exaggerated titles? Methodology: This study analyzed view time, fixations, revisits, and time to first fixation for the graph area, title, y-axis, and x-axis of four line graphs. Qualitative responses were also coded and analyzed. Results: Among other significant findings, this study found that participants spent significantly less time looking at both line graph axes for graphs with a rhetorically exaggerated title than those with a control title. Participants also fixated on and revisited deceptive graphs more so than control graphs, and fixated and revisited the title and x-axis of control graphs significantly more than deceptive graphs. Qualitative results contribute further patterns. Discussion: Findings suggest that graphs with exaggerated titles make viewers less attentive to the axes, but deceptive graphs cause viewers to examine the lines of the graphs themselves in greater detail. Conclusion: Subtle changes in the makeup of graphics can significantly change how viewers examine such visualizations. It is critical to better understand how these changes influence viewing and how they might be leveraged to ultimately impact understanding.