Agent-based model for the h-index - Exact solution

TL;DR

This paper provides an exact analytical solution to an agent-based model of the h-index, improving understanding and simplifying the model, with validation on real-world data.

Contribution

It offers the first exact, analytic formulas for the Ionescu-Chopard agent-based h-index model, enhancing its predictive power and simplicity.

Findings

Exact formulas match simulation results closely.

Simplified model yields a compact h-index formula.

Validated on real-world bibliometric data.

Abstract

The Hirsch's $h$-index is perhaps the most popular citation-based measure of the scientific excellence. In 2013 G. Ionescu and B. Chopard proposed an agent-based model for this index to describe a publications and citations generation process in an abstract scientific community. With such an approach one can simulate a single scientist's activity, and by extension investigate the whole community of researchers. Even though this approach predicts quite well the $h$-index from bibliometric data, only a solution based on simulations was given. In this paper, we complete their results with exact, analytic formulas. What is more, due to our exact solution we are able to simplify the Ionescu-Chopard model which allows us to obtain a compact formula for $h$-index. Moreover, a simulation study designed to compare both, approximated and exact, solutions is included. The last part of this paper presents evaluation of the obtained results on a real-word data set.