The evolution of Complexity co-occurring keywords: bibliometric analysis and network approach

TL;DR

This study combines bibliometric and network analysis to explore how research on Complexity Sciences has evolved across seven disciplines, highlighting shifts from conceptual to applied topics and changes in keyword network structures.

Contribution

It integrates bibliometric and network approaches to analyze keyword co-occurrence, revealing interdisciplinary evolution and topological changes in Complexity Sciences research.

Findings

Increase in complexity-related publications across disciplines

Shift from conceptual to applied complexity topics

Distinct network structures in different research areas

Abstract

Bibliometric studies based on the Web of Science (WOS) database have become an increasingly popular method for analysing the structure of scientific research. So do network approaches, which, based on empirical data, make it possible to characterize the emergence of topological structures over time and across multiple research areas. Our paper is a contribution to interweaving these two lines of research that have progressed in separate ways but whose common applications have been increasingly more frequent. Among other attributes, Author Keywords and Keywords Plus are used as units of analysis that enable us to identify changes in the topics of interest and related bibliography. By considering the co-occurrence of those keywords with the Author Keyword \texttt{Complexity}, we provide an overview of the evolution of studies on Complexity Sciences, and compare this evolution in seven scientific fields. The results show a considerable increase in the number of papers dealing with complexity, as well as a general tendency across different disciplines for this literature to move from a more foundational, general and conceptual to a more applied and specific set of co-occurring keywords. Moreover, we provide evidence of changing topologies of networks of co-occurring keywords, which are described through the computation of some topological coefficients. In so doing, we emphasize the distinguishing structures that characterize the networks of the seven research areas.