Quantifying Long-Term Scientific Impact

TL;DR

This paper introduces a mechanistic model revealing a universal pattern in citation dynamics, enabling better understanding and prediction of long-term scientific impact across disciplines.

Contribution

It presents a unified model for citation trajectories, uncovering universal patterns and providing a new way to measure scientific influence with potential policy relevance.

Findings

Citation histories collapse into a single universal curve

All papers follow a common temporal impact pattern

Model offers reliable long-term impact measures

Abstract

The lack of predictability of citation-based measures frequently used to gauge impact, from impact factors to short-term citations, raises a fundamental question: Is there long-term predictability in citation patterns? Here, we derive a mechanistic model for the citation dynamics of individual papers, allowing us to collapse the citation histories of papers from different journals and disciplines into a single curve, indicating that all papers tend to follow the same universal temporal pattern. The observed patterns not only help us uncover basic mechanisms that govern scientific impact but also offer reliable measures of influence that may have potential policy implications.