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
- Part VI Network Dynamics: Structural Models
- 19 Cascading Behavior in Networks
- 20 The Small-World Phenomenon
- 21s Epidemics
- Part VII Institutions and Aggregate Behavior
- Bibliography
- Index
19 - Cascading Behavior in Networks
from Part VI - Network Dynamics: Structural 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
- Part VI Network Dynamics: Structural Models
- 19 Cascading Behavior in Networks
- 20 The Small-World Phenomenon
- 21s Epidemics
- Part VII Institutions and Aggregate Behavior
- Bibliography
- Index
Summary
Diffusion in Networks
A basic issue in the preceding several chapters has been the way in which an individual's choices depend on what other people do. This has informed our use of information cascades, network effects, and rich-get-richer dynamics to model the processes by which new ideas and innovations are adopted by a population. When we perform this type of analysis, the underlying social network can be considered at two conceptually very different levels of resolution: one in which we view the network as a relatively amorphous population of individuals and look at effects in aggregate, and another in which we move closer to the fine structure of the network as a graph and look at how individuals are influenced by their particular network neighbors. Our focus in these past few chapters has been mainly on the first of these levels of resolution — capturing choices in which each individual is at least implicitly aware of the previous choices made by everyone else, and everyone takes these into account. In the next few chapters, we bring the analysis closer to the detailed network level.
What do we gain by considering this second level of resolution, oriented around network structure? To begin with, we can address a number of phenomena that can't be modeled well at the level of homogeneous populations. Many of our interactions with the rest of the world happen at a local, rather than a global, level: we often don't care as much about the full population's decisions as about the decisions made by friends and colleagues.
- Type
- Chapter
- Information
- Networks, Crowds, and MarketsReasoning about a Highly Connected World, pp. 497 - 536Publisher: Cambridge University PressPrint publication year: 2010
- 4
- Cited by