Can epidemic models describe the diffusion of topics across disciplines?

TL;DR

This paper applies epidemic models to understand how research topics spread across scientific disciplines, using citation networks and a case study on kinesin research to demonstrate the approach's effectiveness.

Contribution

It introduces a novel application of epidemic models to the diffusion of research topics across disciplines using citation networks.

Findings

Epidemic models fit well with empirical data on topic diffusion.

Long incubation periods (4-15.5 years) hinder cross-disciplinary spread.

Citation-based contact networks improve model accuracy.

Abstract

This paper introduces a new approach to describe the spread of research topics across disciplines using epidemic models. The approach is based on applying individual-based models from mathematical epidemiology to the diffusion of a research topic over a contact network that represents knowledge flows over the map of science -as obtained from citations between ISI Subject Categories. Using research publications on the protein class kinesin as a case study, we report a better fit between model and empirical data when using the citation-based contact network. Incubation periods on the order of 4 to 15.5 years support the view that, whilst research topics may grow very quickly, they face difficulties to overcome disciplinary boundaries.