Networks Emerging from Shifts of Interests in Eye-Tracking Records

Network analysis was applied to the eye-tracking data obtained from 20 subjects who read 10 frontal Web pages that were classified into three types of layouts. The network, built for each page, represented the transition of fixations among the segments of a 5x5 mesh imposed on the screen. The core and peripheral nodes were identified by multiple centrality indices as well as the ranking scores and they corresponded fairly well to physical locations of the screen. The clique-based communities revealed interesting patterns that ran counter to ”banner-blind” and that indicated the effects of the three layout types. We presently plan to incorporate a pattern mining technique(s) in hopes of enhancing the present approach.

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

[2]  Qiming Chen,et al.  PrefixSpan,: mining sequential patterns efficiently by prefix-projected pattern growth , 2001, Proceedings 17th International Conference on Data Engineering.

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

[4]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Noriyuki Matsuda,et al.  Visual inspections of the semantic interface on the web: a comparison of top cosmetic brands by SVD and network , 2008 .

[6]  Simon P. Liversedge.  Fixation disparity during reading: Fusion, not suppression , 2008 .

[7]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[8]  Gail Falkingham.  A Whiter Shade of Grey: A new approach to archaeological grey literature using the XML version of the TEI Guidelines , 2005 .

[9]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Jakob Nielsen,et al.  Eyetracking Web Usability , 2009 .

[11]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[12]  Noriyuki Matsuda,et al.  STRUCTURAL COMPARISONS OF THE SEMANTIC INTERFACE OF THE TOP COSMETIC BRANDS ON THE WEB BY NETWORK ANALYSIS , 2011 .

[13]  Joseph H. Goldberg,et al.  Computer interface evaluation using eye movements: methods and constructs , 1999 .

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

[15]  Heike Schaumburg,et al.  Why Are Users Banner-Blind? The Impact of Navigation Style on the Perception of Web Banners , 2006, J. Digit. Inf..

[16]  Réka Albert,et al.  Near linear time algorithm to detect community structures in large-scale networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  Anne R. Haake,et al.  eyePatterns: software for identifying patterns and similarities across fixation sequences , 2006, ETRA.