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The Scalpel or the Shotgun? A Study of Strategies for Boosting New Technology Adoption in Social Network Environments
Author(s) -
Peter Ludlow,
Babak Heydari
Publication year - 2014
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2014.09.051
Subject(s) - betweenness centrality , computer science , selection (genetic algorithm) , centrality , boosting (machine learning) , decision maker , process (computing) , early adopter , operations research , artificial intelligence , mathematics , combinatorics , engineering , operating system
We address the challenge of selecting influential individuals for the marketing of a new product in a social network; we imagine a business attempting to sell a new technology and compare three strategies for selecting seed adopters of the innovation in scale-free networks with the goal of maximizing the adoption within the network. We model the system using a local threshold process for adoption decisions and with a cost associated with creating each seed adopter. We compare random selection, selection of nodes with highest degree and selection of nodes with highest betweenness centrality. We then consider the situation in which the cost of identifying the target nodes is considered; the decision maker must make a trade-off between identifying the best nodes and saving resources for converting the seed nodes to the new technology

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