Exploring information visualization use patterns in casual contexts

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dc.contributor.authorSprague, David William
dc.contributor.supervisorTory, Melanie
dc.date.accessioned2011-07-21T16:44:45Z
dc.date.available2011-07-21T16:44:45Z
dc.date.copyright2011en_US
dc.date.issued2011-07-21
dc.degree.departmentDept. of Computer Scienceen_US
dc.degree.levelDoctor of Philosophy Ph.D.en_US
dc.description.abstractThis dissertation describes a series of studies conducted to explore why people use information visualizations during their non-work time (casual InfoVis) and which factors are critical for visualization adoption and long duration use. I also model typical casual InfoVis usage patterns and provide a framework for future hypothesis testing. Each study explored a different facet of casual InfoVis research and each built on lessons from the previous studies. The first study explored the development and evaluation of a casual InfoVis system, PartyVote, and how visualizations can be used to aid informal group social interactions. Results from the evaluation indicate that the system successfully helped give people a more equal share in choosing music during social gatherings and people could strategically choose music, but social pressures did not constrain behaviors or reduce cheating as much as expected. The complexity of factors affecting PartyVote use led to a pseudo-experiment evaluating the appeal of motion based data encoding. Study results indicated that participants formed distinct opinion-based groups and motion data encoding was only considered appealing to less than half of the participants. Utility was a critical factor for half the participants, but a sizable group still preferred motion use, despite knowing that it reduced system utility. My final study examined how people encountered and used visual representations of data (artifacts) during their non-work time. The artifact study led me to develop the Promoter / Inhibitor Motivation Model (PIMM) of casual visualization interaction. PIMM subsequently helps explain results encountered during the first two studies. The model provides a framework for future casual InfoVis investigations and identifies potential shortfalls and areas of concern when conducting casual InfoVis research. PIMM should also help guide future casual InfoVis system designs.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.bibliographicCitationSprague, D., & Tory, M. (2009). Motivation and Procrastination: Methods for Evaluating Pragmatic Casual Information Visualizations. Visualization Viewpoints article in IEEE Computer Graphics and Applications, vol. 29, no. 4, July 2009, pp. 86-91.en_US
dc.identifier.bibliographicCitationSprague, D., Wu, F., & Tory, M. (2008). Music Selection using the PartyVote Democratic Jukebox. Poster paper in Advanced Visual Interfaces (AVI 2008), pp. 433-436.en_US
dc.identifier.urihttp://hdl.handle.net/1828/3418
dc.languageEnglisheng
dc.language.isoenen_US
dc.rights.tempAvailable to the World Wide Weben_US
dc.subjectCasual Information Visualizationen_US
dc.subjectGrounded Theoryen_US
dc.subjectmotivationen_US
dc.subjecthuman-computer interactionen_US
dc.subjectgoalsen_US
dc.titleExploring information visualization use patterns in casual contextsen_US
dc.typeThesisen_US

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