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    This study deconstructs visual data journalism, revealing inherent tensions between objectivity/subjectivity and humanism/mechanism. These beliefs are shaped by societal forces, not isolated, impacting data storytelling success.

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    Area of Science:

    • Qualitative research methodology
    • Critical theory application in data visualization
    • Sociotechnical analysis of information design

    Background:

    • Visual data journalism integrates journalistic practices with data visualization.
    • Existing research often overlooks the implicit, often contradictory, beliefs underpinning the field.
    • Understanding these beliefs is crucial for advancing data storytelling and visualization research.

    Purpose of the Study:

    • To deconstruct implicit beliefs within visual data journalism using critical theory.
    • To explore the instability of meaning in language used in visual data journalism.
    • To reframe 'success' in visual data storytelling by examining underlying assumptions.

    Main Methods:

    • Qualitative interview study with 17 international visual data journalists.
    • Application of deconstruction approach from literary critique to analyze interview data.
    • Genealogical analysis to contextualize identified beliefs within historical and societal frameworks.

    Main Results:

    • Identified two sets of opposing implicit beliefs: objectivity versus subjectivity, and humanism versus mechanism.
    • Demonstrated that these beliefs are influenced by external societal forces and historical paradigm shifts.
    • Challenged the notion of self-enclosed beliefs within visual data journalism.

    Conclusions:

    • Critical theories like deconstruction and genealogy offer valuable frameworks for analyzing visual data journalism.
    • Reframing 'success' in visual data storytelling requires acknowledging and understanding these implicit beliefs.
    • Diversifying visualization research outcomes necessitates examining the sociotechnical issues surrounding datafication and data visualization.