How Do Viewers Synthesize Conflicting Information from Data Visualizations?
Prateek Mantri (1), Hariharan Subramonyam (2), Audrey L. Michal (3), and Cindy Xiong (1) ((1) University of Massachusetts Amherst, (2) Stanford, University, (3) University of Michigan Ann Arbor)

TL;DR
This study investigates how viewers integrate conflicting information from sequential line chart visualizations, revealing biases in weighting slopes based on their relative direction and steepness, with implications for data storytelling.
Contribution
It provides empirical insights into the cognitive mechanisms of synthesizing conflicting visual data and offers design implications for effective data communication.
Findings
Participants weigh positive slopes more when charts show opposite directions.
Participants favor less steep slopes when charts show the same direction.
The study characterizes synthesis behaviors across different contextual scenarios.
Abstract
Scientific knowledge develops through cumulative discoveries that build on, contradict, contextualize, or correct prior findings. Scientists and journalists often communicate these incremental findings to lay people through visualizations and text (e.g., the positive and negative effects of caffeine intake). Consequently, readers need to integrate diverse and contrasting evidence from multiple sources to form opinions or make decisions. However, the underlying mechanism for synthesizing information from multiple visualizations remains underexplored. To address this knowledge gap, we conducted a series of four experiments (N = 1166) in which participants synthesized empirical evidence from a pair of line charts presented sequentially. In Experiment 1, we administered a baseline condition with charts depicting no specific context where participants held no strong belief. To test for the…
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