Individual differences in gaze patterns for web search

We investigate how people interact with Web search engine result pages using eye-tracking, to provide a detailed understanding of the patterns of user attention. Previous research has examined the visual attention devoted to the 10 organic search results, and we extend this by also examining how gaze is distributed across other components of contemporary search engines, such as ads and related searches. This provides insights about searcher's interactions with the "whole page", and not just individual components. In addition, we used clustering techniques to identify groups of individuals, with distinct gaze patterns. The groups varied in how exhaustively they examined the search results and in what regions of the search result page they paid most attention to (organic results vs. ads). These results further our understanding of how attention is distributed across increasingly complex search result pages, and how individuals exhibit distinct patterns of attention and interaction.

[1]  Meredith Ringel Morris,et al.  What do you see when you're surfing?: using eye tracking to predict salient regions of web pages , 2009, CHI.

[2]  Nigel Ford,et al.  Web search strategies and human individual differences: Cognitive and demographic factors, Internet attitudes, and approaches: Research Articles , 2005 .

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

[4]  Susan T. Dumais,et al.  The good, the bad, and the random: an eye-tracking study of ad quality in web search , 2010, SIGIR.

[5]  Ryen W. White,et al.  Characterizing the influence of domain expertise on web search behavior , 2009, WSDM '09.

[6]  Jacek Gwizdka,et al.  What a difference a tag cloud makes: effects of tasks and cognitive abilities on search results interface use , 2009, Inf. Res..

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

[8]  Thorsten Joachims,et al.  In Google We Trust: Users' Decisions on Rank, Position, and Relevance , 2007, J. Comput. Mediat. Commun..

[9]  Matthew Banta,et al.  What do exploratory searchers look at in a faceted search interface? , 2009, JCDL '09.

[10]  Bryce Allen Individual differences and the conundrums of user-centered design: two experiments , 2000 .

[11]  Ling Xia,et al.  Eye tracking and online search: Lessons learned and challenges ahead , 2008, J. Assoc. Inf. Sci. Technol..

[12]  Tefko Saracevic,et al.  Individual Differences in Organizing, Searching and Retrieving Information. , 1991 .

[13]  Päivi Majaranta,et al.  Eye-Tracking Reveals the Personal Styles for Search Result Evaluation , 2005, INTERACT.

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

[15]  Thorsten Joachims,et al.  Accurately interpreting clickthrough data as implicit feedback , 2005, SIGIR '05.

[16]  Andrew Thatcher,et al.  Information-seeking behaviours and cognitive search strategies in different search tasks on the WWW , 2006 .

[17]  Andrew Howes,et al.  The adaptation of visual search strategy to expected information gain , 2008, CHI.

[18]  David Miller,et al.  Web search strategies and human individual differences: Cognitive and demographic factors, Internet attitudes, and approaches , 2005, J. Assoc. Inf. Sci. Technol..

[19]  George Karypis,et al.  CLUTO - A Clustering Toolkit , 2002 .

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

[21]  Suresh K. Bhavnani,et al.  Important Cognitive Components of Domain-Specific Search Knowledge , 2001, TREC.

[22]  Dan Morris,et al.  Investigating the querying and browsing behavior of advanced search engine users , 2007, SIGIR.

[23]  David Miller,et al.  The role of individual differences in Internet searching: an empirical study , 2001 .