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Telling stories with data -- A systematic review

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arxiv 2312.01164 v1 pith:XOZGBJX4 submitted 2023-12-02 cs.HC cs.GR

classification cs.HCcs.GR
keywords datastorytellingvisualizationarticleinformationreviewsystematicability
verification ladder T0 review T1 audit T2 compute T3 formal
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The exponential growth of data has outpaced human ability to process information, necessitating innovative approaches for effective human-data interaction. To transform raw data into meaningful insights, storytelling, and visualization have emerged as powerful techniques for communicating complex information to decision-makers. This article offers a comprehensive, systematic review of the utilization of storytelling in visualizations. It organizes the existing literature into distinct categories, encompassing frameworks, data and visualization types, application domains, narrative structures, outcome measurements, and design principles. By providing a well-structured overview of this rapidly evolving field, the article serves as a valuable guide for educators, researchers, and practitioners seeking to harness the power of storytelling in data visualization.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Reflecting on Design Paradigms of Animated Data Video Tools

    cs.HC 2025-02 conditional novelty 6.0 of 10

    This CHI paper proposes a two-dimensional framework for classifying 46 data video authoring tools and summarizes design paradigms across components and human-AI roles.

  2. AIED's Unfinished Mission: Centering Agency and Motivation in the Age of Effortless Bypass

    cs.HC 2026-07 conditional novelty 5.5 of 10

    AIED must re-center agency and motivation so learners choose effortful engagement despite easy generative-AI bypass of learning tasks.

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