SNIF-ACT: A cognitive model of user navigation on the World Wide Web

Wai Tat Fu, Peter Pirolli

Research output: Contribution to journalArticlepeer-review


We describe the development of a computational cognitive model that explains navigation behavior on the World Wide Web. The model, called SNIF-ACT (Scent-based Navigation and Information Foraging in the ACT cognitive architecture, is motivated by Information Foraging Theory (IFT), which quantifies the perceived relevance of a Web link to a user's goal by a spreading activation mechanism. The model assumes that users evaluate links on a Web page sequentially and decide to click on a link or to go back to the previous page by a Bayesian satisficing model (BSM) that adaptively evaluates and selects actions based on a combination of previous and current assessments of the relevance of link texts to information goals. SNIF-ACT 1.0 utilizes the measure of utility, called information scent, derived from IFIF to predict rankings of links on different Web pages. The model was tested against a detailed set of protocol data collected from 8 participants as they engaged in two information-seeking tasks using the World Wide Web. The model provided a good match to participants' link selections. In SNIFACT 2.0, we included the adaptive link selection mechanism from the BSM that sequentially evaluates links on a Web page. The mechanism allowed the model to dynamically build up the aspiration levels of actions in a satisficing process (e.g., to follow a link or leave a Web site) as it sequential assessed link texts on a Web page. The dynamic mechanism provides an integrated account of how and when users decide to click on a link or leave a page based on the sequential, ongoing experiences with the link context on current and previous Web pages. SNIFACT 2.0 was validated on a data set obtained from 74 subjects. Monte Carlo simulations of the model showed that SNIFACT 2.0 provided better fits to human data than SNIFACT 1.0 and a Position model that used position of links on a Web page to decide which link to select. We conclude that the combination of the IFT and the BSM provides a good description of user-Web interaction. Practical implications of the model are discussed.

Original languageEnglish (US)
Pages (from-to)355-412
Number of pages58
JournalHuman-Computer Interaction
Issue number4
StatePublished - Dec 10 2007

ASJC Scopus subject areas

  • Applied Psychology
  • Human-Computer Interaction

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