Process / pipelineLibrary Information ScienceInformation behavior / serendipity and incidental acquisitionPipeline

Information Encountering Analysis

Also known as: Information Encountering, Erdelez Information Encountering, Accidental Information Discovery, Incidental Information Acquisition Analysis

OriginatorSanda ErdelezYear1999Sources1Related methods5

Information Encountering Analysis, developed by Sanda Erdelez and articulated in her 1999 Bulletin of the American Society for Information Science article 'Information encountering: It's more than just bumping into information,' studies how people acquire useful information by accident — while searching for something else, or while not searching at all. Against the dominant picture of information behaviour as goal-directed seeking, Erdelez foregrounds serendipitous, incidental discovery as a distinct and important mode. She models an encounter as a sequence of functional steps — noticing, stopping, examining, capturing and returning — and classifies people by how readily they encounter information, from non-encounterers to 'super-encounterers' who experience and exploit accidental discovery frequently. The framework gives a vocabulary and analytic structure for a phenomenon long dismissed as mere luck.

Key highlights

  • Legitimizes and structures the study of serendipitous, incidental information acquisition that goal-directed models ignore.
  • The noticing-stopping-examining-capturing-returning sequence turns a vague notion of serendipity into an analyzable process.
  • Accounts for individual differences through encounterer types, explaining why some people discover far more by accident.
  • Yields concrete design implications for browsing, recommendation and discovery systems that foster useful juxtaposition.

Intuition

This section is available to Pro members. Upgrade to Pro

How it works

This section is available to Pro members. Upgrade to Pro

When to use it

Use Information Encountering Analysis when you want to study or support the acquisition of useful information that people did not deliberately seek — serendipitous discovery in browsing, reading, social interaction or system use — rather than goal-directed search. It is well suited to research on serendipity and creativity in information work, to understanding how people stay aware of developments outside their immediate queries, and to designing browsing, recommendation and discovery environments that encourage beneficial juxtaposition and capture. It is less appropriate for studying narrowly defined known-item retrieval, for tasks where only deliberate search matters, or where you need prevalence estimates of a rare phenomenon. Because encounters are incidental and hard to observe directly, applying the framework usually relies on recalled accounts via interviews, diaries or critical incidents.

Strengths & limitations

Strengths
  • Legitimizes and structures the study of serendipitous, incidental information acquisition that goal-directed models ignore.
  • The noticing-stopping-examining-capturing-returning sequence turns a vague notion of serendipity into an analyzable process.
  • Accounts for individual differences through encounterer types, explaining why some people discover far more by accident.
  • Yields concrete design implications for browsing, recommendation and discovery systems that foster useful juxtaposition.
Limitations
  • Encounters are incidental and largely internal, so they are hard to observe directly and rely on imperfect recall.
  • The encounterer types are descriptive ideal categories without precise measurement or sharp boundaries.
  • Serendipity resists prediction and controlled experiment, limiting causal and quantitative claims.
  • Distinguishing a genuine unsought encounter from low-effort or peripheral searching can be analytically blurry.

Common pitfalls

This section is available to Pro members. Upgrade to Pro

Applications

This section is available to Pro members. Upgrade to Pro

Frequently asked

How does information encountering differ from information seeking?

Information seeking is deliberate, goal-directed pursuit of information to satisfy a recognized need. Information encountering is the opposite in intent: the person acquires useful information they were not looking for — either while searching for something else or while doing something unrelated to searching. The find is unsought yet valuable. Erdelez argues this incidental, serendipitous mode is common and important, and that studying it requires its own framework because the dominant seek-and-retrieve models, built around explicit queries, simply do not describe how accidental discovery happens.

What are the steps of an information encounter?

Erdelez models an encounter as Noticing information in the environment, Stopping the current activity to attend to it, Examining it to judge its relevance, Capturing it by saving, noting or remembering it for later, and Returning to the original task. These functional steps turn a fleeting 'I just stumbled on something useful' moment into an analyzable micro-process. Whether an encounter is fruitful often depends on the examining and capturing steps — recognizing the value of the item and securing it before returning to whatever one was doing.

What is a 'super-encounterer'?

A super-encounterer is a person at the high end of Erdelez's spectrum of encountering propensity — someone who experiences accidental, useful information discovery frequently, actively values it, and builds it into how they work and learn. The typology runs from non-encounterers through occasional and active encounterers to super-encounterers, capturing the substantial individual differences in serendipitous behaviour. Super-encounterers tend to keep many background problems primed and to scan their environment in ways that make relevant unsought information register, which is why they discover far more by 'accident' than others do.

Sources

  1. 1.
    Erdelez, S. (1999). Information encountering: It's more than just bumping into information. Bulletin of the American Society for Information Science, 25(3), 26-29.

You have read it. What now?

Cite this page

ScholarGate. (2026, June 23). Information Encountering Analysis. ScholarGate. https://scholargate.app/library-information-science/information-encountering-analysis