An eye-tracking study of information usage in Web search : Variations in target position and contextual snippet length

Web search services are among the most heavily used applications on the World Wide Web. Perhaps because search is used in such a huge variety of tasks and contexts, the user interface must strike a careful balance to meet all user needs. We describe a study that used eye tracking methodologies to explore the effects of changes in the presentation of search results. We found that adding information to the contextual snippet significantly improved performance for informational tasks but degraded performance for navigational tasks. We discuss possible reasons for this difference and the design implications for the better presentation of search results. The studies reported here are to be published in CHI 2007[13, 13]. Author

[1]  Craig Silverstein,et al.  Analysis of a Very Large Altavista Query Log" SRC Technical note #1998-14 , 1998 .

[2]  Eric Horvitz,et al.  Patterns of search: analyzing and modeling Web query refinement , 1999 .

[3]  W. Pratt,et al.  The usefulness of dynamically categorizing search results. , 2000, Journal of the American Medical Informatics Association : JAMIA.

[4]  Susan T. Dumais,et al.  Optimizing search by showing results in context , 2001, CHI.

[5]  Bernard J. Jansen,et al.  A review of web searching studies and a framework for future research , 2001 .

[6]  Robert W. Reeder,et al.  Information scent as a driver of Web behavior graphs: results of a protocol analysis method for Web usability , 2001, CHI.

[7]  Ed H. Chi,et al.  Using information scent to model user information needs and actions and the Web , 2001, CHI.

[8]  Andrei Broder,et al.  A taxonomy of web search , 2002, SIGF.

[9]  Anthony J. Hornof,et al.  Cognitive strategies and eye movements for searching hierarchical computer displays , 2003, CHI '03.

[10]  Jimmy J. Lin,et al.  The role of context in question answering systems , 2003, CHI Extended Abstracts.

[11]  Kevin Li,et al.  Faceted metadata for image search and browsing , 2003, CHI '03.

[12]  Mark S. Ackerman,et al.  The perfect search engine is not enough: a study of orienteering behavior in directed search , 2004, CHI.

[13]  Anthony Jameson,et al.  Depth- and breadth-first processing of search result lists , 2004, CHI EA '04.

[14]  Daniel E. Rose,et al.  Understanding user goals in web search , 2004, WWW '04.

[15]  Andrew Howes,et al.  Good Enough But I'll Just Check: Web-page Search as Attentional Refocusing , 2004, ICCM.

[16]  Gary Marchionini,et al.  Evaluation and evolution of a browse and search interface: relation browser , 2005, DG.O.

[17]  Andrew T. Duchowski,et al.  Using Eye Tracking to Evaluate Alternative Search Results Interfaces , 2005 .

[18]  Zhenyu Liu,et al.  Automatic identification of user goals in Web search , 2005, WWW '05.

[19]  Thorsten Joachims,et al.  Accurately Interpreting Clickthrough Data as Implicit Feedback , 2017 .

[20]  Mark Levene,et al.  Associating search and navigation behavior through log analysis , 2005, J. Assoc. Inf. Sci. Technol..

[21]  Thorsten Joachims,et al.  The influence of task and gender on search and evaluation behavior using Google , 2006, Inf. Process. Manag..

[22]  Susan T. Dumais,et al.  Searching to eliminate personal information management , 2006, CACM.

[23]  Daniel E. Rose.  Reconciling information-seeking behavior with search user interfaces for the Web , 2006 .

[24]  Edward Cutrell,et al.  An eye tracking study of the effect of target rank on web search , 2007, CHI.

[25]  Edward Cutrell,et al.  What are you looking for?: an eye-tracking study of information usage in web search , 2007, CHI.