A Time-based Visualization for Web User Classification in Social Networks

Andrew Brunker, Quang Nguyen, Anthony Maeder, Rhys Tague, Gregory Kolt, Trevor Savage, Corneel Vandelanotte, Mitch Duncan, Cristina Caperchione, Richard Rosenkranz, Anetta Van Itallie, W Mummery

    Research output: Contribution to conferencePaperpeer-review

    Abstract

    This paper presents a new visual analytics framework for analyzing health-related physical activity data. Existing techniques mostly rely on node-links visualizations to represent the usage patterns as social networks. This work takes a different approach that provides interactive scatter-plot visualizations on classified and time-based data. By providing a flexible visualization that can provide different angles on the multidimensional and classified data, the analyst could have better understanding and insight on web user behavior compared to the traditional social network methods. The effectiveness of our method has been demonstrated with a case study on an online portal system for tracking passive physical activity, called Walk 2.0.

    Original languageEnglish
    Pages9-18
    Number of pages10
    DOIs
    Publication statusPublished - 5 Aug 2014
    EventProceedings of the 7th International Symposium on Visual Information Communication and Interaction -
    Duration: 5 Aug 2014 → …

    Conference

    ConferenceProceedings of the 7th International Symposium on Visual Information Communication and Interaction
    Period5/08/14 → …

    Keywords

    • Classification
    • Information visualization
    • Physical activity
    • Scatter plot
    • Visual analytics

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