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Impact of the Network Structure on the SIR Model Spreading Phenomena in Online Networks

Authors:
Marek Opuszko
Johannes Ruhland

Keywords: online social networks, information diffusion

Abstract:
We present an analysis of how the spreading phenomena, which includes the spread of information, innovations, ideas, trends, etc. is influenced by the structure of the underlying (social) network. We conducted spreading simulations using the SIR (Susceptible-Infected-Recovered) model on a large number of real-world and artificially generated network datasets. The results show that the network characteristics have a significant effect on the SIR diffusion. The results reveal that the network structure affects the diffusion in terms of the achieved diffusion, the course of the diffusion and the predictability of the diffusion. We could also show that the effect of other parameters, such as the impact of seeding (network targeting), significantly differs in relationship to the underlying network structure. With these findings, we are able to provide a more differentiated picture on previous contradictory findings, especially in the field of seeding strategies. We further provide useful recommendations for future research to make results more generalizable and comparable.

Pages: 22 to 28

Copyright: Copyright (c) IARIA, 2013

Publication date: July 21, 2013

Published in: conference

ISSN: 2308-4529

ISBN: 978-1-61208-283-7

Location: Nice, France

Dates: from July 21, 2013 to July 26, 2013