A SIR epidemic model for citation dynamics

TL;DR

This paper applies an SIR epidemic model to understand citation dynamics of scientific papers, revealing insights into community size and impact, and correlating epidemiological parameters with journal impact factors.

Contribution

It introduces a mechanistic SIR model to analyze citation patterns, providing new insights into citation community size and impact estimation.

Findings

Good agreement between epidemiological parameters and journal impact factors

Estimated community sizes for citing papers

Insights into the impact of well-cited papers

Abstract

The study of citations in the scientific literature crosses the boundaries between the traditional branches of science and stands on its own as a most profitable research field dubbed the `science of science'. Although the understanding of the citation histories of individual papers involves many intangible factors, the basic assumption that citations beget citations can explain most features of the empirical citation patterns. Here we use the SIR epidemic model as a mechanistic model for the citation dynamics of well-cited papers published in selected journals of the American Physical Society. The estimated epidemiological parameters offer insight on unknown quantities as the size of the community that could cite a paper and its ultimate impact on that community. We find a good, though imperfect, agreement between the rank of the journals obtained using the epidemiological parameters and the impact factor rank.