A mechanism for evolution of the physical concepts network

TL;DR

This paper investigates the growth mechanisms of a scientific concepts network, analyzing empirical data from physics preprints and proposing a combined model of block growth and preferential selection to explain its structure.

Contribution

It introduces a novel mechanism combining block growth and preferential selection to explain the evolution of the concepts network, supported by empirical analysis.

Findings

Network characteristics cannot be explained by simple growth models.

A combined model of block growth and preferential selection fits empirical data.

The structure emerges from the synergy of both growth factors.

Abstract

We suggest an underlying mechanism that governs the growth of a network of concepts, a complex network that reflects the connections between different scientific concepts based on their co-occurrences in publications. To this end, we perform empirical analysis of a network of concepts based on the preprints in physics submitted to the arXiv.org. We calculate the network characteristics and show that they cannot follow as a result of several simple commonly used network growth models. In turn, we suggest that a simultaneous account of two factors, i.e., growth by blocks and preferential selection, gives an explanation of empirically observed properties of the concepts network. Moreover, the observed structure emerges as a synergistic effect of these both factors: each of them alone does not lead to a satisfactory picture.