In this study we investigate the utility of using mouse clicks as an alternative for eye fixations in the context of understanding data visualizations. We developed a crowdsourced study online in which participants were presented with a series of images containing graphs and diagrams and asked to describe them. Each image was blurred so that the participant needed to click to reveal bubbles - small, circular areas of the image at normal resolution. This is similar to having a confined area of focus like the human eye fovea. We compared the bubble click data with the fixation data from a complementary eye-tracking experiment by calculating the similarity between the resulting heatmaps. A high similarity score suggests that our methodology may be a viable crowdsourced alternative to eye-tracking experiments, especially when little to no eye-tracking data is available. This methodology can also be used to complement eye-tracking studies with an additional behavioral measurement, since it is specifically designed to measure which information people consciously choose to examine for understanding visualizations.
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Nam Wook Kim, Zoya Bylinskii, Michelle A. Borkin, Aude Oliva, Krzysztof Z. Gajos, and Hanspeter Pfister. A crowdsourced alternative to eye-tracking for visualization understanding. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, CHI EA '15, pages 1349-1354, New York, NY, USA, 2015. ACM.
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