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Updated: Aug 27, 2025

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    Adding more text to charts, including statistical and relational details, enhances reader understanding and preference. Even heavily annotated charts are preferred over text alone, guiding better visualization design.

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    Area of Science:

    • Information Visualization
    • Human-Computer Interaction
    • Data Presentation

    Background:

    • Visualizations effectively convey information but often require accompanying text for context.
    • Limited experimental data exists on optimal text quantity, quality, and placement in charts.
    • Individual preferences vary between visual and textual data representations.

    Purpose of the Study:

    • To investigate the impact of textual annotations on chart comprehension and user preference.
    • To determine the optimal amount, semantic content, and placement of text in data visualizations.
    • To provide evidence-based guidelines for integrating text and charts.

    Main Methods:

    • 302 participants evaluated univariate line charts with varying text annotations.
    • Participants ranked charts based on preference and described information takeaways.
    • Textual content varied in amount and semantic focus (elemental, encoded, statistical, relational).

    Main Results:

    • Heavily annotated charts were preferred over those with less text or text alone.
    • Text describing statistical or relational components led to more statistical/relational takeaways.
    • Text placement significantly influenced information takeaway, with titles and proximity to data being key.

    Conclusions:

    • Increased textual annotations in charts do not negatively impact user preference and can enhance understanding.
    • The semantic content and placement of text are crucial for effective data communication.
    • Four design guidelines are proposed for optimizing text-visualization integration.