Category: Tier 3 - Decision-Making Traits Scale: 0.0 (weak scent-following) to 1.0 (strong scent-following)

Definition

Information Foraging describes how users navigate by following "information scent" -- cues that signal the chance of finding desired content on a given path. Adapted from optimal foraging theory in ecology, this trait models which links users click, when they stay or leave, and how they split attention across sources.

High foragers follow strong scent trails fast and leave weak paths quickly. Low foragers may stick with weak trails or miss strong cues. This leads to poor navigation.

Research Foundation

Primary Citation

"Information foraging theory is an approach to understanding how strategies and technologies for information seeking, gathering, and consumption are adapted to the flux of information in the environment... The notion of information scent is used to explain how people assess the utility or relevance of information sources, and how they select navigation paths." — Pirolli & Card, 1999, p. 643

Full Citation (APA 7): Pirolli, P., & Card, S. K. (1999). Information foraging. Psychological Review, 106(4), 643-675.

DOI: https://doi.org/10.1037/0033-295x.106.4.643

Supporting Research

"Users follow information scent to navigate the web. When scent is strong, users are more efficient. When scent is weak or misleading, they become lost and frustrated." — Chi et al., 2001, p. 498

Full Citation (APA 7): Chi, E. H., Pirolli, P., Chen, K., & Pitkow, J. (2001). Using information scent to model user information needs and actions on the web. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 490-497.

DOI: https://doi.org/10.1145/365024.365325

Key Numerical Values

Metric	Value	Source
Average page dwell time before abandonment	10-20 seconds	Nielsen (2011)
Probability of following highest-scent link	0.62	Chi et al. (2001)
Back button usage with weak scent	39% higher	Cockburn & McKenzie (2001)
Scent strength predicts task success	r = 0.71	Pirolli & Card (1999)
Users scan 20% of page for scent cues	mean fixation	Nielsen (2006)
Optimal patch-leaving threshold	2-3 failed predictions	ACT-IF model (Pirolli, 2007)

Behavioral Levels

Value	Label	Behaviors
0.0-0.2	Poor Forager	Fails to recognize relevant link text; persists on irrelevant pages too long; clicks randomly when uncertain; ignores navigation breadcrumbs; exhaustive rather than selective reading; high back-button usage; frequently "lost" in sites
0.2-0.4	Weak Forager	Sometimes follows weak scent trails; slow to recognize dead-ends; occasional relevant selections; may be misled by ambiguous labels; moderate exploration efficiency; needs redundant cues
0.4-0.6	Moderate Forager	Adequate scent detection in clear environments; recognizes strong cues but may miss subtle ones; reasonable patch-leaving decisions; some unnecessary exploration; effective with well-designed navigation
0.6-0.8	Strong Forager	Quickly identifies high-scent options; efficient navigation path selection; abandons low-value pages promptly; uses multiple scent cues (text, images, position); rarely backtracks unnecessarily
0.8-1.0	Expert Forager	Near-optimal information seeking; immediately recognizes scent patterns; predicts content accurately from cues; minimal wasted navigation; instinctively uses site architecture; very low back-button usage

Web Behavior Patterns

Link Selection

Strong Foragers (0.7-1.0):

Select links matching query terms
Use link position as additional cue
Notice snippet/preview text
Prefer specific over generic labels
Rapid confident selections

Weak Foragers (0.0-0.3):

Random or sequential link selection
Ignore descriptive text
Click "Contact" when seeking products
Miss clearly-labeled navigation
Hesitant, exploratory clicking

Patch-Leaving Behavior

The "patch" in foraging theory is analogous to a web page or site section:

Strong Foragers:

Leave pages with weak scent within 5-10 seconds
Recognize when information gain has diminished
Move to higher-yield areas quickly
Efficient depth vs breadth decisions

Weak Foragers:

Stay on low-yield pages 30+ seconds
Re-read content hoping for relevance
Deep navigation into wrong branches
Reluctant to "give up" on dead ends

Search Result Processing

Strong Foragers:

Rapid snippet scanning
Click based on content prediction
Skip irrelevant domains immediately
Use search refinement efficiently

Weak Foragers:

Sequential top-to-bottom clicking
Poor prediction from snippets
Click all results regardless of relevance
Rarely refine search queries

Information Scent Components

Scent Source	Description	Weight
Link Text	Words in clickable anchor	High
Surrounding Context	Text near the link	Medium
Visual Design	Icons, colors, prominence	Medium
Position	Navigation location, F-pattern	Medium
Preview/Tooltip	Hover information	Low-Medium
Domain/URL	Site credibility signals	Low

Estimated Trait Correlations

Correlation estimates are derived from related research findings and theoretical models. Empirical calibration is planned (GitHub #95).

Related Trait	Correlation	Mechanism
Trait-Comprehension	r = 0.48	Understanding text enables scent detection
Trait-ReadingTendency	r = 0.39	Scanners may miss scent cues
Trait-WorkingMemory	r = 0.31	Holding goal enables scent evaluation
Trait-Patience	r = 0.28	Patient users may persist despite weak scent
Trait-Satisficing	r = -0.44	Strong foragers optimize paths
Trait-Curiosity	r = 0.24	Curious users explore adjacent scent

Persona Values

Persona	Information Foraging Value	Rationale
Power User	0.90	Expert at recognizing interface patterns
Tech Enthusiast	0.85	Familiar with web conventions
Rushed Professional	0.75	Efficient by necessity
First-Time User	0.35	Lacks pattern recognition experience
Elderly Novice	0.30	Unfamiliar with web conventions
Distracted Teen	0.50	Knows patterns but attention divided
Careful Senior	0.45	Methodical but may miss cues
Anxious User	0.40	Anxiety impairs efficient processing
Overwhelmed Parent	0.55	Experience exists but cognitive load interferes

Design Implications

Strengthening Information Scent

Descriptive link text - "View pricing plans" not "Click here"
Consistent labeling - Same terms in navigation and content
Progressive disclosure - Preview information on hover
Visual hierarchy - Important links visually prominent
Breadcrumbs - Show current location in hierarchy
Search suggestions - Guide toward high-scent paths

Accommodating Weak Foragers

Redundant cues - Multiple ways to find content
Clear error recovery - Easy backtracking
Search prominence - Alternative to navigation
Related links - Suggest adjacent content
Wizard patterns - Guided linear paths

Measurement in CBrowser

// Information foraging affects navigation decisions
function selectLink(availableLinks: Link[], goal: string, traits: Traits): Link {
  const scentScores = availableLinks.map(link =>
    calculateScent(link, goal)
  );

  if (traits.informationForaging > 0.7) {
    // Strong forager: select highest scent
    return availableLinks[argmax(scentScores)];
  } else if (traits.informationForaging > 0.4) {
    // Moderate: probabilistic selection weighted by scent
    return weightedRandom(availableLinks, scentScores);
  } else {
    // Weak forager: may select randomly or sequentially
    return random() > 0.5 ? availableLinks[0] : randomChoice(availableLinks);
  }
}

// Patch-leaving decision
function shouldLeavePage(timeOnPage: number, contentRelevance: number, traits: Traits): boolean {
  const threshold = 10 + (1 - traits.informationForaging) * 20; // 10-30 seconds
  const relevanceThreshold = 0.3 + traits.informationForaging * 0.4; // 0.3-0.7

  return timeOnPage > threshold && contentRelevance < relevanceThreshold;
}

Bibliography

Chi, E. H., Pirolli, P., Chen, K., & Pitkow, J. (2001). Using information scent to model user information needs and actions on the web. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 490-497. https://doi.org/10.1145/365024.365325

Cockburn, A., & McKenzie, B. (2001). What do web users do? An empirical analysis of web use. International Journal of Human-Computer Studies, 54(6), 903-922. https://doi.org/10.1006/ijhc.2001.0459

Nielsen, J. (2006). F-shaped pattern for reading web content. Nielsen Norman Group. https://www.nngroup.com/articles/f-shaped-pattern-reading-web-content/

Nielsen, J. (2011). How long do users stay on web pages? Nielsen Norman Group. https://www.nngroup.com/articles/how-long-do-users-stay-on-web-pages/

Pirolli, P. (2007). Information foraging theory: Adaptive interaction with information. Oxford University Press.

Pirolli, P., & Card, S. K. (1999). Information foraging. Psychological Review, 106(4), 643-675. https://doi.org/10.1037/0033-295x.106.4.643

Spool, J. M., Perfetti, C., & Brittan, D. (2004). Designing for the scent of information. User Interface Engineering.

Copyright: (c) 2026 Alexa Eden.

License: MIT License

Contact: [email protected]

Trait InformationForaging