Book contents
- Frontmatter
- Contents
- Preface
- 1 Overview
- Part I Graph Theory and Social Networks
- Part II Game Theory
- Part III Markets and Strategic Interaction in Networks
- Part IV Information Networks and the World Wide Web
- Part V Network Dynamics: Population Models
- 16 Information Cascades
- 17 Network Effects
- 18 Power Laws and Rich-Get-Richer Phenomena
- Part VI Network Dynamics: Structural Models
- Part VII Institutions and Aggregate Behavior
- Bibliography
- Index
16 - Information Cascades
from Part V - Network Dynamics: Population Models
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- 1 Overview
- Part I Graph Theory and Social Networks
- Part II Game Theory
- Part III Markets and Strategic Interaction in Networks
- Part IV Information Networks and the World Wide Web
- Part V Network Dynamics: Population Models
- 16 Information Cascades
- 17 Network Effects
- 18 Power Laws and Rich-Get-Richer Phenomena
- Part VI Network Dynamics: Structural Models
- Part VII Institutions and Aggregate Behavior
- Bibliography
- Index
Summary
Following the Crowd
When people are connected by a network, it becomes possible for them to influence each other's behavior and decisions. In the next several chapters, we will explore how this basic principle gives rise to a range of social processes in which networks serve to aggregate individual behavior and thus produce population-wide, collective outcomes.
There is a nearly limitless set of situations in which people are influenced by others: in the opinions they hold, the products they buy, the political positions they support, the activities they pursue, the technologies they use, and many other things. What we'd like to do here is to go beyond this observation and consider some of the reasons why such influence occurs. We'll see that there are many settings in which it may in fact be rational for an individual to imitate the choices of others even if the individual's own information suggests an alternative choice.
As a first example, suppose that you are choosing a restaurant in an unfamiliar town, and based on your own research about restaurants, you intend to go to restaurant A. However, when you arrive you see that no one is eating in restaurant A, whereas restaurant B next door is nearly full. If you believe that other diners have tastes similar to yours, and that they too have some information about where to eat, it may be rational to join the crowd at B rather than to follow your own information. To see how this is possible, suppose that each diner has obtained independent but imperfect information about which of the two restaurants is better.
- Type
- Chapter
- Information
- Networks, Crowds, and MarketsReasoning about a Highly Connected World, pp. 425 - 448Publisher: Cambridge University PressPrint publication year: 2010
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