Pioneers of Influence Propagation in Social Networks View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2014

AUTHORS

Kumar Gaurav , Bartłomiej Błaszczyszyn , Paul Holger Keeler

ABSTRACT

In this paper, we present a diffusion model developed by enriching the generalized random graph (a.k.a. configuration model), motivated by the phenomenon of viral marketing in social networks. The main results on this model are rigorously proved in [3], and in this paper we focus on applications. Specifically, we consider random networks having Poisson and Power Law degree distributions where the nodes are assumed to have varying attitudes towards influence propagation, which we encode in the model by their transmitter degrees. We link a condition involving total degree and transmitter degree distributions to the effectiveness of a marketing campaign. This suggests a novel approach to decision-making by a firm in the context of viral marketing which does not depend on the detailed information of the network structure. More... »

PAGES

626-636

Book

TITLE

Computing and Combinatorics

ISBN

978-3-319-08782-5
978-3-319-08783-2

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-08783-2_54

DOI

http://dx.doi.org/10.1007/978-3-319-08783-2_54

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1013030163


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