On the Behavior of Journal Impact Factor Rank-Order Distribution

TL;DR

This paper discovers an empirical law governing the rank-order distribution of journal impact factors across diverse scientific disciplines, providing a better fit than existing models.

Contribution

It introduces a new empirical law for journal impact factor rank-order behavior, validated across multiple scientific fields with superior fitting performance.

Findings

The empirical law fits impact factor data well across various disciplines.

The model outperforms other rank-order models in accuracy.

Extensions to other knowledge areas are discussed.

Abstract

An empirical law for the rank-order behavior of journal impact factors is found. Using an extensive data base on impact factors including journals on Education, Agrosciences, Geosciences, Biosciences and Environ- mental, Chemical, Computer, Engineering, Material, Mathematical, Medical and Physical Sciences we have found extremely good fits out- performing other rank-order models. Some extensions to other areas of knowledge are discussed.