Growth and dynamics of Econophysics: A bibliometric and network analysis

TL;DR

This study analyzes the growth, collaboration patterns, and network properties of the Econophysics discipline from 2000 to 2019 using bibliometric and network analysis methods, revealing key contributors and structural characteristics.

Contribution

It provides a comprehensive bibliometric and network analysis of Econophysics, highlighting growth trends, collaboration dynamics, and the small-world nature of the discipline's network.

Findings

China leads in publication count and national collaboration.

The author collaboration network exhibits a power-law distribution.

The network demonstrates small-world properties with an average path length of 5.

Abstract

Digitization of publications, advancement in communication technology, and the availability of bibliographic data have made it easier for the researchers to study the growth and dynamics of any discipline. We present a study on "Econophysics" metadata extracted from the Web of Science managed by the Clarivate Analytics from 2000-2019. The study highlights the growth and dynamics of the discipline by measures of a number of publications, citations on publications, other disciplines contribution, institutions participation, country-wise spread, etc. We investigate the impact of self-citations on citations with every five-year interval. Also, we find the contribution of other disciplines by analyzing the cited references. Results emerged from micro, meso and macro-level analysis of collaborations show that the distributions among authors collaboration and affiliations of authors follow a power law. Thus, very few authors keep producing most of the papers and are from a few institutions. We find that China is leading in the production of a number of authors and a number of papers; however, shares more of national collaboration rather than international, whereas the USA shares more international collaboration. Finally, we demonstrate the evolution of the author's collaborations and affiliations networks from 2000-2019. Overall the analysis reveals the "small-world" property of the network with average path length 5. As a consequence of our analysis, this study can serve as in-depth knowledge to understand the growth and dynamics of the Econophysics network both qualitatively and quantitatively.