Peter Pirolli
Stuart K. Card
Abstract
The Hyperbolic Tree is a focus + context information visualization that has been developed to amplify users' ability to navigate large tree-structured information systems. Information scent is a theoretical construct that captures one kind of interaction between task and display. Information scent is provided by task-relevant display cues, such as node labels on a tree that influence a user's visual search behavior and navigation decisions. An empirical Accuracy of Scent (AOS) score was developed to characterize a set of tasks that required users to find (Retrieval Tasks) or compare (Comparison Tasks) information in tree structures. Two experiments investigated the effect of information scent (tasks with different AOS scores) on performance with the Hyperbolic Tree Browser and the Microsoft Windows File Browser, which is a widely available conventional browser. Experiment 1 found no overall difference in performance time between the two browsers, but did reveal a marginal interaction of information scent with browser performance on Retrieval Tasks. On high AOS tasks the Hyperbolic showed faster performance, but on low AOS tasks the Windows File Browser showed faster performance. Experiment 2 focused only on the Retrieval tasks and revealed that Hyperbolic Tree users examined more tree nodes at a faster rate and visually searched through the tree hierarchy at a faster rate than users of a Windows File Browser lookalike, however, visual search paths were shortened in dense areas of the Hyperbolic Tree display when information scent was low. Two processes appear to affect visual search in the Hyperbolic display: strong information scent improves visual search, and the crowding of targets in a compressed region degrades visual search especially when there is weak information scent.
- Bell, W. J. 1991. Searching Behavior: The Behavioral Ecology of Finding Resources. Chapman and Hall, London.Google Scholar
- Card, S., Pirolli, P., Van Der Wege, M., Morrison, J., Reeder, R., Schraedley, P., and Boshart, J. 2001. Information scent as a driver of Web behavior graphs: Results of a protocol analysis method for Web usability. In Proceedings of Human Factors in Computing Systems (Seattle, WA). Google Scholar
- Card, S. K., Mackinlay, J. D., and Schneiderman, B. 1999. Information Visualization: Using Vision to Think. Morgan-Kaufmann, San Francisco. Google Scholar
- Card, S. K., Robertson, G. G., and Mackinlay, J. D. 1991. The information visualizer: An information workspace. In Proceedings of Conference on Human Factors in Computing Systems, CHI '91 (New Orleans). Google Scholar
- Chi, E., Pirolli, P., Chen, K., and Pitkow, J. E. 2001. Using information scent to model user needs and actions on the Web. In Proceedings of Human Factors in Computing Systems, CHI 2001 (Seattle). Google Scholar
- Chi, E., Pirolli, P., and Pitkow, J. 2000. The scent of a site: A system for analyzing and predicting information scent, usage, and usability of a Web site. In Proceedings of Human Factors in Computing Systems, CHI 2000 (The Hague). Google Scholar
- Chun, M. M., and Wolfe, J. M. 1996. Just say no: How are visual searches terminated when there is no target present? Cogn. Psychol. 30, 39--78.Google Scholar
- Clark, H. H. 1973. The language-as-fixed-effect fallacy: A critique of language statistics in psychological research. J. Verbal Learn. Verbal Behav. 12, 335--359.Google Scholar
- Czerwinski, M. and Larson, K. 1997. The new Web browsers: They're cool but are they useful? In People and Computers XII: Proceedings of the HCI '97 Conference, H. Thimbleby, B. O'Conaill, and P. Thomas, Eds. Springer Verlag, Berlin.Google Scholar
- Drury, C. G. and Clement, M. R. 1978. The effect of area, density, and number of background characters on visual search. Hum. Factors 20, 597--602.Google Scholar
- Furnas, G. W. 1997. Effective view navigation. In Proceedings of Human Factors in Computing Systems, CHI '97 (Atlanta). Google Scholar
- Huberman, B. A. and Hogg, T. 1987. Phase transitions in artificial intelligence systems. Artif. Intell. 33, 155--171. Google Scholar
- Lamping, J. and Rao, R. 1994. Laying out and visualizing large trees using a hyperbolic space. In Proceedings of UIST '94 (Marina del Rey, CA). Google Scholar
- Lamping, J., Rao, R., and Pirolli, P. 1995. A focus + context technique based on hyperbolic geometry for visualizing large hierarchies. In Proceedings of CHI '95, ACM Conference on Human Factors in Computing Systems. ACM, New York. Google Scholar
- Logan, G. D. 1996. The CODE theory of visual attention. Psychol. Rev. 103, 603--649.Google Scholar
- Mackinlay, J. D., Robertson, G. G., and Card, S. K. 1991. The perspective wall: Detail and context smoothly integrated. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. ACM, New York. Google Scholar
- Mullet, K., Fry, C., and Schiano, D. 1997. On your marks, get set, browse! In Proceedings of Human Factors in Computing Systems, CHI '97 (Extended Abstracts, Atlanta). Google Scholar
- Pirolli, P. 1997. Computational models of information scent-following in a very large browsable text collection. In Proceedings of the Conference on Human Factors in Computing Systems, CHI '97 (Atlanta). Google Scholar
- Pirolli, P. 1998. Exploring browser design trade-offs using a dynamical model of optimal information foraging. In Proceedings of the Conference on Human Factors in Computing Systems, CHI '98 (Los Angeles). Google Scholar
- Pirolli, P. and Card, S. K. 1999. Information foraging. Psychol. Rev. 106, 643--675.Google Scholar
- Pirolli, P., Card, S., and Van Der Wege, M. 2001. Visual information foraging in a focus+context visualization. In Proceedings of the Human Factors in Computing Systems, CHI 2001 (Seattle). Google Scholar
- Raaijmakers, J. G. W., Schrijnemakers, J. M. C., and Gremmen, F. 1999. How to deal with "The language-as-fixed-effect fallacy": Common misconceptions and alternative solutions. J. Memory Lang. 41, 416--426.Google Scholar
- Resnikoff, H. L. 1989. The Illusion of Reality. Springer-Verlag, New York. Google Scholar
- Robertson, G. G., Card, S. K., and Mackinlay, J. D. 1993. Information visualization using 3D interactive animation. Commun. ACM 36, 57--71. Google Scholar
- Stephens, D. W. and Krebs, J. R. 1986. Foraging Theory. Princeton University Press, Princeton, N.J.Google Scholar
- Tullis, T. S. 1985. A computer-based tool for evaluating alphanumeric displays. In Interact '84, B. Shackel, Ed. Elsevier Science, Amsterdam, 719--723.Google Scholar
- User Interface Engineering. 1999. Designing Information-Rich Web Sites. Author, Cambridge, MA.Google Scholar
- Ware, C. 1999. Information Visualization: Perception for Design. Morgan-Kaufmann, San Francisco. Google Scholar
- Wolfe, J. M. 1994. Guided Search 2.0: A revised model of visual search. Psychonom. Bull. Rev. 1, 202--238.Google Scholar
- Wolfe, J. M. 1998. What can 1 million trials tell us about visual search? Psychol. Sci. 9, 33--39.Google Scholar
- Woodruff, A., Faulring, A., Rosenholtz, R., Morrison, J., and Pirolli, P. 2001. Using thumbnails to search the Web. In Proceedings of the Conference on Human Factors in Computing Systems, CHI 2001 (Seattle). Google Scholar
Index Terms
- The effects of information scent on visual search in the hyperbolic tree browser
Recommendations
The scent of a site: a system for analyzing and predicting information scent, usage, and usability of a Web site
CHI '00: Proceedings of the SIGCHI conference on Human Factors in Computing SystemsDesigners and researchers of users' interactions with the World Wide Web need tools that permit the rapid exploration of hypotheses about complex interactions of user goals, user behaviors, and Web site designs. We present an architecture and system for ...
Using information scent to model user information needs and actions and the Web
CHI '01: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsOn the Web, users typically forage for information by navigating from page to page along Web links. Their surfing patterns or actions are guided by their information needs. Researchers need tools to explore the complex interactions between user needs, ...
Information scent as a driver of Web behavior graphs: results of a protocol analysis method for Web usability
CHI '01: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsThe purpose of this paper is to introduce a replicable WWW protocol analysis methodology illustrated by application to data collected in the laboratory. The methodology uses instrumentation to obtain detailed recordings of user actions with a browser, ...
Comments