Agreement in Dynamic Map Segmentation: Effects of Framing and Change Salience

Event segmentation theory, which explores how individuals divide continuousexperiences into discrete events, has been extensively studied in naturalisticstimuli. We investigate whether key findings from event segmentation rese?arch generalize to animated data visualizations, specifically dynamic thema?tic maps. Experiment 1 showed that inter-individual segmentation agreementin dynamic maps occurs above chance levels and is influenced by the directionof the depicted trend. Experiments 2 and 3 build on these findings by syste?matically varying the depicted trend in maps showing population changes offictional insect species on islands. In addition, Experiments 2 and 3 exami?ned how conceptual (framing of the species as endangered or invasive) andperceptual factors (salience of directional change) interact to shape segmen?tation agreement. In Experiment 2, salience was manipulated through the useof different color scales: Saturation-based scales as the high-salience conditi?on and hue-based scales as the low-salience condition. We found a significantthree-way interaction between trend, framing, and salience: agreement washigher when the framing matched the trend direction, but only in the high?salience condition. In Experiment 3, salience was more subtly manipulatedby showing the trend either spatially clustered (high salience) or spatiallydistributed (low salience) across the maps. The results partly replicate thefindings of Experiment 2, showing a significant interaction between trend,framing, and spatial pattern on segmentation agreement, with higher agree?ment for negative trends, particularly when population decline was madesalient and framed as endangered. Overall, these findings extend event seg?mentation theory to abstract data visualizations, demonstrating that theirsegmentation is modulated by both bottom-up perceptual features and top?down conceptual expectations.