Rewiring the network. What helps an innovation to diffuse?

Authored by Katarzyna Sznajd-Weron, Rafal Weron, Janusz Szwabinski

Date Published: 2014-03

DOI: 10.1088/1742-5468/2014/03/p03007

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

A fundamental question related to innovation diffusion is flow the structure of the social network influences the process. Empirical evidence regarding real-world networks of influence is very limited. On the other hand, agent-based modeling literature reports different, and at times seemingly Contradictory, results. In this paper we study innovation diffusion processes for a range of Watts-Strogatz networks in an attempt to shed more light on this problem. Using the so-called Sznajd model as the backbone of opinion dynamics, We find that the published results are in fact consistent and allow us to predict the role of network topology in various situations. In particular, the diffusion of in is easier on more regular graphs, i.e. with a higher clustering coefficient. Moreover, in the case of uncertainty which is particularly high for innovations connected to public health programs or ecological campaigns a more clustered network will help the diffusion. On the other hand, when social influence is less important (i.e. ill the case of per information), a shorter path will help the innovation to spread in the society and as a result the diffusion will be easiest on a random graph.

Tags

interacting agent models networks critical phenomena of socio-economic systems random graphs socio-economic networks