Investigating the Effect of Hyperlink Information Scent on Users’ Interaction with a Web Site

  • Nikolaos Tselios
  • Christos Katsanos
  • Nikolaos Avouris
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5727)

Abstract

In the study presented in this paper we investigate how variations of information scent of hyperlinks of a webpage influence users’ behavior in terms of attention-focusing, confidence, effectiveness and efficiency, while exploring a website. In the reported study, 19 participants completed eight different tasks associated with eight simplified websites. Analysis of the results showed that even small differences in the target-link’s information scent can substantially affect users’ performance, distribution of attention and confidence. The study contributes to the related literature by quantifying the impact of even small differences in the target-link’s scent on users’ success ratio, time for first click, confidence and distribution of attention. In addition, a scent threshold value was identified, below which all the measured variables were substantially affected, and thus the link could be characterized as of “weak scent”.

Keywords

Information scent eye tracking study Latent Semantic Analysis 

References

  1. 1.
    Blackmon, M., Kitajima, M., Polson, P.: Tool for accurately predicting website navigation problems, non-problems, problem severity, and effectiveness of repairs. In: Proceedings of CHI 2005, pp. 31–40. ACM Press, New York (2005)Google Scholar
  2. 2.
    Card, S., Pirolli, P., Wege, M., Morrison, J., Reeder, R.W., Schraedley, P., Boshart, J.: Information scent as a driver of Web behavior graphs: results of a protocol analysis method for Web usability. In: Proceedings of the CHI 2001, pp. 498–505. ACM Press, New York (2001)Google Scholar
  3. 3.
    Chi, E., Rosien, A., Supattanasiri, G., Williams, A., Royer, C., Chow, C., Robles, E., Dalal, B., Chen, J., Cousins, S.: The Bloodhound Project: Automating Discovery of Web Usability Issues using the InfoScent Simulator. In: Proceedings CHI 2003, pp. 505–512. ACM Press, New York (2003)Google Scholar
  4. 4.
    Habuchi, Y., Kitajima, M., Takeuchi, H.: Comparison of eye movements in searching for easy-to-find and hard-to-find information in a hierarchically organized information structure. In: Proceedings of ETRA 2008, Savannah, Georgia, pp. 131–134. ACM Press, New York (2008)Google Scholar
  5. 5.
    Katsanos, C., Tselios, N., Avouris, N.: InfoScent evaluator: a semi-automated tool to evaluate semantic appropriateness of hyperlinks in a web site. In: Proceedings of OZCHI 2006, Sydney, Australia, pp. 373–376. ACM Press, New York (2006)Google Scholar
  6. 6.
    Landauer, T.K., Dumais, S.: A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review 104(2), 211–240 (1997)CrossRefGoogle Scholar
  7. 7.
    Pirolli, P.: Information Foraging Theory: Adaptive Interaction with Information. Oxford University Press, USA (2007)CrossRefGoogle Scholar
  8. 8.
    Miller, C.S., Remington, R.W.: Modeling information navigation: implications for information architecture. Human-Computer Interaction 19(3), 225–271 (2004)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Nikolaos Tselios
    • 1
  • Christos Katsanos
    • 1
  • Nikolaos Avouris
    • 1
  1. 1.Human-Computer Interaction Group, Department of Electrical and Computer EngineeringUniversity of PatrasRio PatrasGreece

Personalised recommendations