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Proposes a framework to assess visualization complexity, revealing insights for effective science communication.
As citizens increasingly rely on data to navigate complex scientific issues, effective visualization has become essential. This study proposes a multidimensional framework to assess visualization complexity. We collected 6,641 COVID-19 visualizations from 29 media outlets over 18 months and recruited U.S. participants ( N = 905) to evaluate a subset ( N = 640). Results indicate that traditional measures of visual complexity had limited effects on audience perceptions, whereas data encodings, particularly advanced chart types and higher variable count, significantly shaped audience evaluations. These findings offer practical insights for enhancing the clarity and effectiveness of data visualizations in science communication.
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Yilang Peng (2026) studied this question.
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