Persuasive Visualization

Persuasive Visualization is a type of data visualization designed to influence an audience's beliefs or decisions by strategically emphasizing specific aspects of the data through visual encoding, narrative structure, and rhetorical techniques, distinguishing it from neutral or purely exploratory visualizations.

24

Publications

1.4K

Citations

71

Authors

37

Institutions

Publications per year

2017–2026

13

Authors

71

  1. HQ
    Huamin Qu

    Hong Kong University of Science and Technology, Hong Kong SAR China

    3 publications · 108 citations

    3

    h-index

  2. MX
    Meng Xia

    Hong Kong University of Science and Technology, Hong Kong SAR China

    2 publications · 51 citations

    2

    h-index

  3. NK
    Nirmal Kumar Raveendranath

    Indiana University – Purdue University Indianapolis, United States

    1 publications · 28 citations

    1

    h-index

  4. NH
    Nicholas H. Lurie

    University of Connecticut, United States

    1 publications · 21 citations

    1

    h-index

  5. RL
    Rosemary Lucy Hill

    University of Leeds, United Kingdom

    1 publications · 271 citations

    1

    h-index

1–5 of 71

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 4 publications · 382 citations

    4

    h-index

  2. Information Communication & Society

    ICS · 1 publications · 271 citations

    1

    h-index

  3. Cultural Sociology

    1 publications · 30 citations

    1

    h-index

  4. Journal of Baltic Science Education

    JBSE · 1 publications · 15 citations

    1

    h-index

  5. Proceedings of the ACM on Human-Computer Interaction

    PACMHCI · 1 publications · 32 citations

    1

    h-index

1–5