An Opinion Dynamics Model for the Diffusion of Innovations

TL;DR

This paper introduces a model for the spread of innovations based on opinion dynamics, analyzing how social network structure influences adoption timing and final adoption rates, with predictions matching empirical data.

Contribution

It presents a novel opinion dynamics model for innovation diffusion that accounts for neighbor influence and network effects, including small world properties.

Findings

Fat-tailed distribution for late adopters predicted and empirically verified

Initial adopter placement affects diffusion dynamics

Small world network effects influence final adoption proportion

Abstract

We study the dynamics of the adoption of new products by agents with continuous opinions and discrete actions (CODA). The model is such that the refusal in adopting a new idea or product is increasingly weighted by neighbor agents as evidence against the product. Under these rules, we study the distribution of adoption times and the final proportion of adopters in the population. We compare the cases where initial adopters are clustered to the case where they are randomly scattered around the social network and investigate small world effects on the final proportion of adopters. The model predicts a fat tailed distribution for late adopters which is verified by empirical data.