The persuasive power of data visualization

Anshul Vikram Pandey, Anjali Manivannan, Oded Nov, Margaret Satterthwaite, Enrico Bertini

    Research output: Contribution to journalArticle

    Abstract

    Data visualization has been used extensively to inform users. However, little research has been done to examine the effects of data visualization in influencing users or in making a message more persuasive. In this study, we present experimental research to fill this gap and present an evidence-based analysis of persuasive visualization. We built on persuasion research from psychology and user interfaces literature in order to explore the persuasive effects of visualization. In this experimental study we define the circumstances under which data visualization can make a message more persuasive, propose hypotheses, and perform quantitative and qualitative analyses on studies conducted to test these hypotheses. We compare visual treatments with data presented through barcharts and linecharts on the one hand, treatments with data presented through tables on the other, and then evaluate their persuasiveness. The findings represent a first step in exploring the effectiveness of persuasive visualization.

    Original languageEnglish (US)
    Article number6876023
    Pages (from-to)2211-2220
    Number of pages10
    JournalIEEE Transactions on Visualization and Computer Graphics
    Volume20
    Issue number12
    DOIs
    StatePublished - Dec 31 2014

    Fingerprint

    Data visualization
    Visualization
    User interfaces

    Keywords

    • elaboration likelihood model
    • evaluation
    • Persuasive visualization

    ASJC Scopus subject areas

    • Computer Graphics and Computer-Aided Design
    • Software
    • Computer Vision and Pattern Recognition
    • Signal Processing

    Cite this

    Pandey, A. V., Manivannan, A., Nov, O., Satterthwaite, M., & Bertini, E. (2014). The persuasive power of data visualization. IEEE Transactions on Visualization and Computer Graphics, 20(12), 2211-2220. [6876023]. https://doi.org/10.1109/TVCG.2014.2346419

    The persuasive power of data visualization. / Pandey, Anshul Vikram; Manivannan, Anjali; Nov, Oded; Satterthwaite, Margaret; Bertini, Enrico.

    In: IEEE Transactions on Visualization and Computer Graphics, Vol. 20, No. 12, 6876023, 31.12.2014, p. 2211-2220.

    Research output: Contribution to journalArticle

    Pandey, AV, Manivannan, A, Nov, O, Satterthwaite, M & Bertini, E 2014, 'The persuasive power of data visualization', IEEE Transactions on Visualization and Computer Graphics, vol. 20, no. 12, 6876023, pp. 2211-2220. https://doi.org/10.1109/TVCG.2014.2346419
    Pandey AV, Manivannan A, Nov O, Satterthwaite M, Bertini E. The persuasive power of data visualization. IEEE Transactions on Visualization and Computer Graphics. 2014 Dec 31;20(12):2211-2220. 6876023. https://doi.org/10.1109/TVCG.2014.2346419
    Pandey, Anshul Vikram ; Manivannan, Anjali ; Nov, Oded ; Satterthwaite, Margaret ; Bertini, Enrico. / The persuasive power of data visualization. In: IEEE Transactions on Visualization and Computer Graphics. 2014 ; Vol. 20, No. 12. pp. 2211-2220.
    @article{609ef44c27db4a3d8da65f0228dad93a,
    title = "The persuasive power of data visualization",
    abstract = "Data visualization has been used extensively to inform users. However, little research has been done to examine the effects of data visualization in influencing users or in making a message more persuasive. In this study, we present experimental research to fill this gap and present an evidence-based analysis of persuasive visualization. We built on persuasion research from psychology and user interfaces literature in order to explore the persuasive effects of visualization. In this experimental study we define the circumstances under which data visualization can make a message more persuasive, propose hypotheses, and perform quantitative and qualitative analyses on studies conducted to test these hypotheses. We compare visual treatments with data presented through barcharts and linecharts on the one hand, treatments with data presented through tables on the other, and then evaluate their persuasiveness. The findings represent a first step in exploring the effectiveness of persuasive visualization.",
    keywords = "elaboration likelihood model, evaluation, Persuasive visualization",
    author = "Pandey, {Anshul Vikram} and Anjali Manivannan and Oded Nov and Margaret Satterthwaite and Enrico Bertini",
    year = "2014",
    month = "12",
    day = "31",
    doi = "10.1109/TVCG.2014.2346419",
    language = "English (US)",
    volume = "20",
    pages = "2211--2220",
    journal = "IEEE Transactions on Visualization and Computer Graphics",
    issn = "1077-2626",
    publisher = "IEEE Computer Society",
    number = "12",

    }

    TY - JOUR

    T1 - The persuasive power of data visualization

    AU - Pandey, Anshul Vikram

    AU - Manivannan, Anjali

    AU - Nov, Oded

    AU - Satterthwaite, Margaret

    AU - Bertini, Enrico

    PY - 2014/12/31

    Y1 - 2014/12/31

    N2 - Data visualization has been used extensively to inform users. However, little research has been done to examine the effects of data visualization in influencing users or in making a message more persuasive. In this study, we present experimental research to fill this gap and present an evidence-based analysis of persuasive visualization. We built on persuasion research from psychology and user interfaces literature in order to explore the persuasive effects of visualization. In this experimental study we define the circumstances under which data visualization can make a message more persuasive, propose hypotheses, and perform quantitative and qualitative analyses on studies conducted to test these hypotheses. We compare visual treatments with data presented through barcharts and linecharts on the one hand, treatments with data presented through tables on the other, and then evaluate their persuasiveness. The findings represent a first step in exploring the effectiveness of persuasive visualization.

    AB - Data visualization has been used extensively to inform users. However, little research has been done to examine the effects of data visualization in influencing users or in making a message more persuasive. In this study, we present experimental research to fill this gap and present an evidence-based analysis of persuasive visualization. We built on persuasion research from psychology and user interfaces literature in order to explore the persuasive effects of visualization. In this experimental study we define the circumstances under which data visualization can make a message more persuasive, propose hypotheses, and perform quantitative and qualitative analyses on studies conducted to test these hypotheses. We compare visual treatments with data presented through barcharts and linecharts on the one hand, treatments with data presented through tables on the other, and then evaluate their persuasiveness. The findings represent a first step in exploring the effectiveness of persuasive visualization.

    KW - elaboration likelihood model

    KW - evaluation

    KW - Persuasive visualization

    UR - http://www.scopus.com/inward/record.url?scp=84910084203&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84910084203&partnerID=8YFLogxK

    U2 - 10.1109/TVCG.2014.2346419

    DO - 10.1109/TVCG.2014.2346419

    M3 - Article

    VL - 20

    SP - 2211

    EP - 2220

    JO - IEEE Transactions on Visualization and Computer Graphics

    JF - IEEE Transactions on Visualization and Computer Graphics

    SN - 1077-2626

    IS - 12

    M1 - 6876023

    ER -