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Quantifying Visualization Vibes: Measuring Socio-Indexicality at Scale.

Amy Rae Fox, Michelle Morgenstern, Graham M Jones

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    Summary
    This summary is machine-generated.

    Visualizations convey more than explicit data, communicating social provenance. Design elements interact with data to shape these beyond-data interpretations, impacting trust and public understanding.

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    Area of Science:

    • Information Visualization
    • Sociology of Visualization
    • Human-Computer Interaction

    Background:

    • Visualizations possess a socio-indexical function, communicating beyond explicit data.
    • Prior research examines public discourse surrounding data visualizations.

    Purpose of the Study:

    • To develop an analytic framework for describing inferences about an artifact's social provenance.
    • To investigate how design features influence these 'beyond-data' readings.

    Main Methods:

    • Conducted attribution-elicitation surveys.
    • Analyzed descriptive evidence of social inferences.

    Main Results:

    • Social inferences from visualizations can be studied asynchronously.
    • These inferences are not limited by sociocultural group or data literacy.
    • Inferences about social provenance can influence trust assessments.
    • Design features, topic, and data messages interact to create 'beyond-data' readings.

    Conclusions:

    • Inferences about social provenance have significant design and research implications.
    • Broadening visualization research to include sociocultural phenomena offers actionable design recommendations.
    • Addressing challenges in public data communication requires understanding these broader impacts.