Rewiring the network. What helps an innovation to diffuse?

Abstract

Abstract. A fundamental question related to innovation diffusion is how the social network structure influences the process. Empirical evidence regarding real-world influence networks 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 to predict the role of network topology in various situations. In particular, the diffusion of innovation 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. in the case of perfect 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.

Mapping the q-voter model: From a single chain to complex networks

“…In the modified version, repetitions are forbidden, which is probably more sociologically justified. Moreover, q influencing agents may form panels of different kinds, including structures proposed in [12,26], which is also different from the original formulation of the model. This in turn allows to investigate the role of the group structure.…”

“…More details on the dynamic rules of the model may be found in Ref. [26]. It is worth to stress here the difference between the modified q-voter model with independence p ≥ 0 and the original q-voter model with ǫ ≥ 0 [6].…”

“…Therefore, the original q-voter model with p = 0 is not suitable to model e.g. diffusion of innovation, for which the initial state with all spinsons down (unadopted) is a typical one [26].…”

“…1 six different groups of influence on a complex network are schematically shown. We would like to stress here that the choice of precisely such groups is not accidental and is dictated mainly by earlier papers [6,12,26,20]:…”

“…There are already several attempts to generalize the q-voter model to complex networks [12,24,25,26]. However, as shown in Ref.…”