Comparing scanning behaviour in web search on small and large screens

Although web search on mobile devices is common, little is known about how users read search result lists on a small screen. We used eye tracking to compare users' scanning behaviour of web search engine result pages on a small screen (hand-held devices) and a large screen (desktops or laptops). The objective was to determine whether search result pages should be designed differently for mobile devices. To compare scanning behaviour, we considered only the fixation time and scanning strategy using our new method called 'Trackback'. The results showed that on a small screen, users spend relatively more time to conduct a search than they do on a large screen, despite tending to look less far ahead beyond the link that they eventually select. They also show a stronger tendency to seek information within the top three results on a small screen than on a large screen. The reason for this tendency may be difficulties in reading and the relative location of page folds. The results clearly indicated that scanning behaviour during web search on a small screen is different from that on a large screen. Thus, research efforts should be invested in improving the presentation of search engine result pages on small screens, taking scanning behaviour into account. This will help provide a better search experience in terms of search time, accuracy of finding correct links, and user satisfaction.

[1]  Hiroshi Sato,et al.  MobiGaze: development of a gaze interface for handheld mobile devices , 2010, CHI EA '10.

[2]  Thorsten Joachims,et al.  Eye-tracking analysis of user behavior in WWW search , 2004, SIGIR '04.

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

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

[5]  Amanda Spink,et al.  How are we searching the World Wide Web? A comparison of nine search engine transaction logs , 2006, Inf. Process. Manag..

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

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

[8]  Claude Ghaoui,et al.  Encyclopedia of Human Computer Interaction , 2005 .

[9]  Mark Levene,et al.  Associating search and navigation behavior through log analysis: Research Articles , 2005 .

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

[11]  Susan T. Dumais,et al.  Individual differences in gaze patterns for web search , 2010, IIiX.

[12]  Bing Pan,et al.  The determinants of web page viewing behavior: an eye-tracking study , 2004, ETRA.

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

[14]  Albrecht Schmidt,et al.  Eye-gaze interaction for mobile phones , 2007, Mobility '07.

[15]  Andreas Dengel,et al.  Reading and estimating gaze on smart phones , 2012, ETRA '12.

[16]  Yoram Singer,et al.  Learning to Order Things , 1997, NIPS.

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

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

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