Abstract
This study tested whether systematic associations between colors and concepts can be used to infer meaning from visual displays. It is well-known from the Stroop Effect that people are faster at reading a color word when displayed in a congruent text color than in an incongruent color (e.g. “RED” in red ink vs. green ink). However, it is unknown whether this type of facilitation/interference generalizes to abstract associations in ecologically valid domains. We addressed this question within the domain of recycling. We first tested whether participants have systematic associations between colors and to-be-discarded items: paper, glass and trash (Experiment 1). For each object, participants rated how strongly they associated it with each of the Berkeley Color Project 37 colors. White was systematically associated with paper, light blue with glass, and black with trash. In Experiment 2, we tested whether a different group of participants was better at discarding trash/recyclables in bins whose colors were consistent with empirically-derived mappings from Experiment 1 (color-concept consistent) than in bins whose colors were determined from ecologically-based mappings of trash/recycling bins in their environment (Brown University). During each trial participants saw a display of three bins colored in an empirically-based or an ecologically-based color scheme, along with the name of an object (paper, glass or trash). They were instructed to choose which bin was appropriate for discarding the object. The bins were not labeled so participants could only rely on their color intuitions to complete the task. Trials included all combinations of each object (paper/glass/trash) with each color scheme (color positions counterbalanced). Participants were faster and more accurate at discarding objects in the empirically-based colored bins scheme than in ecologically-based bins. The results suggest that not only do people have strong color-concept associations, but color-coding according to those associations facilitates inferring meaning from visual displays.
Meeting abstract presented at VSS 2015