A Population Model for the Academic Ecosystem

TL;DR

This paper introduces a population model for the academic ecosystem based on publication data, capturing researcher lifecycle, growth, and productivity to inform better bibliometric indices and resource management.

Contribution

It proposes a generalized branching process model to describe academic community evolution, addressing systemic inflation and researcher lifecycle in the literature.

Findings

Model captures researcher lifecycle stages and productivity patterns.

Provides insights into academic ecosystem growth and inflation.

Suggests implications for bibliometric index development.

Abstract

In recent times, the academic ecosystem has seen a tremendous growth in number of authors and publications. While most temporal studies in this area focus on evolution of co-author and citation network structure, this systemic inflation has received very little attention. In this paper, we address this issue by proposing a population model for academia, derived from publication records in the Computer Science domain. We use a generalized branching process as an overarching framework, which enables us to describe the evolution and composition of the research community in a systematic manner. Further, the observed patterns allow us to shed light on researchers' lifecycle encompassing arrival, academic life expectancy, activity, productivity and offspring distribution in the ecosystem. We believe such a study will help develop better bibliometric indices which account for the inflation, and also provide insights into sustainable and efficient resource management for academia.