Motion in casual InfoVis and the interrelation between personality, performance, and preference

Current real-world casual information visualization systems use motion to presumably increase system appeal and repeated use. Despite empirical evidence suggesting that motion is distracting and not particularly good for data encoding, its continued use may indicate benefits independent of traditional utility measures. We present two experiments designed to highlight differences and disparities between task performance, perceived system utility, and subject preference for static and moving glyphs. A music library visualization provided a casual, practical, nuanced, and pertinent domain application. Song glyphs represented beats per minute and beat strength using a line encircling the glyph. Beat encodings used one of four methods: a static sinusoidal pattern (static), an oscillating movement pattern (motion), an oscillating sinusoidal line (redundant), and a sinusoidal line that moves to the currently playing song (extraneous). Subjects first performed a pair-wise glyph comparison task to identify conditional differences in speed and accuracy. Then, a more realistic playlist generation task was performed using these beat encodings to explore opinions and behavioral patterns using a qualitative approach. Our results show clear performance decreases associated with motion use in the comparison task. Despite this, more than half the subjects preferred a moving glyph to the static encoding. We identified three groups of subjects (utility, fun, and intuitive) where subjects were consistent within groups but distinctly different between groups. This suggests that casual visualizations could be customizable based on high level groupings, where pragmatism can be emphasized for some users and aesthetics and style can be enhanced for others.

[1]  Danah Boyd,et al.  Vizster: visualizing online social networks , 2005, IEEE Symposium on Information Visualization, 2005. INFOVIS 2005..

[2]  Andrea Bunt,et al.  Matching attentional draw with utility in interruption , 2007, CHI.

[3]  Jeffrey Heer,et al.  Animated Transitions in Statistical Data Graphics , 2007, IEEE Transactions on Visualization and Computer Graphics.

[4]  Barbara Tversky,et al.  Animation: can it facilitate? , 2002, Int. J. Hum. Comput. Stud..

[5]  George Tzanetakis,et al.  HUMAN PERCEPTION AND COMPUTER EXTRACTION OF MUSICAL BEAT STRENGTH , 2002 .

[6]  Lyn Bartram,et al.  Can motion increase user interface bandwidth in complex systems? , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[7]  Thomas W. Calvert,et al.  Moticons: : detection, distraction and task , 2003, Int. J. Hum. Comput. Stud..

[8]  George Tzanetakis,et al.  Musical genre classification of audio signals , 2002, IEEE Trans. Speech Audio Process..

[9]  Benjamin B. Bederson,et al.  Does animation help users build mental maps of spatial information? , 1999, Proceedings 1999 IEEE Symposium on Information Visualization (InfoVis'99).

[10]  Colin Ware,et al.  Supporting Visual Queries on Medium-Sized Node–Link Diagrams , 2005, Inf. Vis..

[11]  D. Norman The psychology of everyday things , 1990 .

[12]  John T. Stasko,et al.  Effectiveness of Animation in Trend Visualization , 2008, IEEE Transactions on Visualization and Computer Graphics.

[13]  M. Sheelagh T. Carpendale,et al.  Grounded evaluation of information visualizations , 2008, BELIV.

[14]  D. Norman The psychology of everyday things", Basic Books Inc , 1988 .

[15]  D. Norman Emotional design : why we love (or hate) everyday things , 2004 .

[16]  Carl Gutwin,et al.  Can smooth view transitions facilitate perceptual constancy in node-link diagrams? , 2007, GI '07.

[17]  Melanie Tory,et al.  Music selection using the PartyVote democratic jukebox , 2008, AVI '08.

[18]  John T. Stasko,et al.  Casual Information Visualization: Depictions of Data in Everyday Life , 2007, IEEE Transactions on Visualization and Computer Graphics.

[19]  Tamara Munzner,et al.  Steerable, Progressive Multidimensional Scaling , 2004, IEEE Symposium on Information Visualization.

[20]  M. Anshel,et al.  Effect of music and rhythm on physical performance. , 1978, Research quarterly.

[21]  Colin Ware,et al.  Motion coding for pattern detection , 2006, APGV '06.