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Creating Emordle: Animating Word Cloud for Emotion Expression.

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    This summary is machine-generated.

    Emordle animates word clouds to convey emotion, using animation randomness and speed to adjust intensity. User studies confirmed its effectiveness in expressing emotions like happiness, sadness, anger, and fear.

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    Area of Science:

    • Human-Computer Interaction
    • Information Visualization
    • Affective Computing

    Background:

    • Word clouds are compact text visualizations but lack emotional context.
    • Existing animated texts and word clouds offer limited strategies for emotional expression.

    Purpose of the Study:

    • To introduce emordle, a conceptual design for animating word clouds to convey emotional context.
    • To develop a framework for users to create emotionally expressive word clouds.

    Main Methods:

    • Reviewed online animated texts and word clouds to identify emotion injection strategies.
    • Introduced a composite animation approach using entropy (randomness) and speed.
    • Designed proof-of-concept emordles for happiness, sadness, anger, and fear.
    • Conducted crowdsourcing studies to evaluate emotion perception and parameter effectiveness.
    • Performed a user study to assess the framework's usability and effectiveness.

    Main Results:

    • Animations effectively conveyed intended emotions, with general agreement among viewers.
    • Animation entropy and speed parameters allowed for fine-tuning emotion intensity.
    • Users successfully created emordles expressing intended emotions using the proposed framework.

    Conclusions:

    • Emordle provides an effective method for visualizing and conveying emotion through animated word clouds.
    • The identified animation factors (entropy and speed) are crucial for controlling emotional expression.
    • Future research can explore broader applications of emotion expression in data visualization.