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A time-based visualization for web user classification in social networks

conference contribution
posted on 06.12.2017, 00:00 by A Brunker, Q Nguyen, R Tague, G Kolt, T Savage, Corneel Vandelanotte, Mitchell Duncan, Cristina Caperchione, R Rosenkranz, A Maeder
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.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

98

End Page

105

Number of Pages

8

Start Date

01/01/2014

Finish Date

01/01/2014

ISBN-13

9781450327657

Location

Sydney, Australia

Publisher

ACM Press

Place of Publication

New York, NY

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Institute for Health and Social Science Research (IHSSR); Kansas State University; Not affiliated to a Research Institute; School of Human, Health and Social Sciences (2013- ); University of Alberta; University of British Columbia; University of Western Sydney;

Era Eligible

Yes

Name of Conference

International Symposium on Visual Information Communication and Interaction

Usage metrics

CQUniversity

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