NDLI: Maximizing influence in a competitive social network: a follower's perspective

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Maximizing influence in a competitive social network: a follower's perspective

Content Provider	ACM Digital Library
Author	Wild, Stefan M. van Zuylen, Anke Nagarajan, Chandrashekhar Carnes, Tim
Abstract	We consider the problem faced by a company that wants to use viral marketing to introduce a new product into a market where a competing product is already being introduced. We assume that consumers will use only one of the two products and will influence their friends in their decision of which product to use. We propose two models for the spread of influence of competing technologies through a social network and consider the influence maximization problem from the follower's perspective. In particular we assume the follower has a fixed budget available that can be used to target a subset of consumers and show that, although it is NP-hard to select the most influential subset to target, it is possible to give an efficient algorithm that is within 63% of optimal. Our computational experiments show that by using knowledge of the social network and the set of consumers targeted by the competitor, the follower may in fact capture a majority of the market by targeting a relatively small set of the right consumers.
Starting Page	351
Ending Page	360
Page Count	10
File Format	PDF
ISBN	9781595937001
DOI	10.1145/1282100.1282167
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-08-19
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Network analysis Viral marketing Approximation algorithms Social networks Targeted marketing
Content Type	Text
Resource Type	Article

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