Information Foraging: A Theory of How People Navigate on the Web - NN/G
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Information Foraging: A Theory of How People Navigate on the Web
Raluca Budiu
Raluca Budiu
November 10, 2019
2019-11-10
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Summary:<br>To decide whether to visit a page, people take into account how much relevant information they are likely to find on that page relative to the effort involved in extracting that info.
Will people scroll on a webpage? How do they decide to click on a link? When do they leave a webpage? When do they prefer to search and when do they browse? How do they decide to search for information in a mobile app or on the web?
These and many other questions about web-user behaviors can be answered by the information-foraging theory.
In this article we present a broad overview of the theory and review some of its implications for web design.
In This Article:
Analogy with Animal Foraging Behavior
What Is Information Foraging?
Information Scent
Costs of Addressing an Information Need
Enrichments
Good User Experience Can Make Enrichments Unnecessary
Conclusion
Reference
Analogy with Animal Foraging Behavior
Information foraging was developed at PARC (former XEROX PARC) by Peter Pirolli and Stuart Card in the late 1990s and was inspired by animal behavior theories about how animals forage for food (hence the name). Thus, not surprisingly, animal-foraging and information-foraging theories share common terminology, as listed in the table below.
ANIMAL FORAGING
INFORMATION FORAGING
Food
Goal
Information
A site containing one or more potential sources of food
Patch
A website (or other source of information)
Search for food
Forage
Search for information
The animal’s assessment of how likely it is that a given patch will provide food
Scent
How promising a potential source of information appears to the user
The totality of food types that an animal may consider in order to satisfy hunger
Diet
The totality of the information sources that a user may consider in order to satisfy an information need
ANIMAL FORAGING
INFORMATION FORAGING
Food
Goal
Information
A site containing one or more potential sources of food
Patch
A website (or other source of information)
Search for food
Forage
Search for information
The animal’s assessment of how likely it is that a given patch will provide food
Scent
How promising a potential source of information appears to the user
The totality of food types that an animal may consider in order to satisfy hunger
Diet
The totality of the information sources that a user may consider in order to satisfy an information need
What Is Information Foraging?
Information foraging is the fundamental theory of how people navigate on the web to satisfy an information need. It essentially says that, when users have a certain information goal, they assess the information that they can extract from any candidate source of information relative to the cost involved in extracting that information and choose one or several candidate sources so that they maximize the ratio:
Rate of gain = Information value / Cost associated with obtaining that information
In other words, if people have a question, they will decide which webpage to go to based on (1) how likely it is that the page will provide an answer to their question, and (2) how long it’s going to take to get the answer if they go to that page.
(Animal-behavior science shows that a similar type of optimization holds true for animal foraging — hence, the optimal foraging theory that served as source of inspiration for Pirolli and Card. Basically, an animal needs to eat more calories than it expends, or it will starve and ultimately die without offspring. Across many generations, animals have evolved highly optimized food-foraging strategies.)
In layman terms, information foraging explains why people don’t scroll mindlessly or click on every single link on the page: because they attempt to maximize the rate of gain and get as much relevant information in as little time as possible. Scrolling or clicking a lot more would probably gain the user more information, but in the user’s estimation, the rate-of-gain ratio would decrease, because the numerator (the information value) would increase too little compared to the increase in the denominator (the interaction cost associated to getting the information).
You may wonder how people can be so rational as to always take the action that maximizes their gain. After all, we have countless examples of people behaving irrationally, against their own interest. In fact, human behavior can be well described by what Nobel-prize winner Herbert Simon called bounded rationality. Whereas the choices that people make attempt to maximize benefit and minimize cost, humans have a hard time precisely estimating benefit and cost and thus...