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24 - Cascading Behavior in Networks: Algorithmic and Economic Issues

from IV - Additional Topics

Published online by Cambridge University Press:  31 January 2011

Jon Kleinberg
Affiliation:
Department of Computer Science Cornell University
Noam Nisan
Affiliation:
Hebrew University of Jerusalem
Tim Roughgarden
Affiliation:
Stanford University, California
Eva Tardos
Affiliation:
Cornell University, New York
Vijay V. Vazirani
Affiliation:
Georgia Institute of Technology
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Summary

Abstract

The flow of information or influence through a large social network can be thought of as unfolding with the dynamics of an epidemic: as individuals become aware of new ideas, technologies, fads, rumors, or gossip, they have the potential to pass them on to their friends and colleagues, causing the resulting behavior to cascade through the network.

We consider a collection of probabilistic and game-theoretic models for such phenomena proposed in the mathematical social sciences, as well as recent algorithmic work on the problem by computer scientists. Building on this, we discuss the implications of cascading behavior in a number of online settings, including word-of-mouth effects (also known as “viral marketing”) in the success of new products, and the influence of social networks in the growth of online communities.

Introduction

The process by which new ideas and new behaviors spread through a population has long been a fundamental question in the social sciences. New religious beliefs or political movements; shifts in society that lead to greater tolerance or greater polarization; the adoption of new technological, medical, or agricultural innovations; the sudden success of a new product; the rise to prominence of a celebrity or political candidate; the emergence of bubbles in financial markets and their subsequent implosion – these phenomena all share some important qualitative properties.

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Publisher: Cambridge University Press
Print publication year: 2007

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