THE EVOLUTION OF COMPLEXITY CO-OCCURRING KEYWORDS: BIBLIOMETRIC ANALYSIS AND NETWORK APPROACH

ARAÚJO Tanya, Alexandre Abreu () and LOUÇÃ Francisco
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ARAÚJO Tanya: Lisbon School of Economics and Management (ISEG), University of Lisbon, Lisbon, Portugal†Research Unit on Complexity in Economics (UECE), Research in Economics and Mathematics (REM), Lisbon, Portugal
LOUÇÃ Francisco: Lisbon School of Economics and Management (ISEG), University of Lisbon, Lisbon, Portugal†Research Unit on Complexity in Economics (UECE), Research in Economics and Mathematics (REM), Lisbon, Portugal

Advances in Complex Systems (ACS), 2024, vol. 27, issue 04n05, 1-23

Abstract: Bibliometric studies based on the Web of Science (WOS) database have become an increasingly popular method for analyzing 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 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 Complexity, we provide an overview of the evolution of studies on Complexity Sciences, and compare this evolution in seven social and natural 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, specific and empirical 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.

Keywords: Complex systems; complexity; bibliometrics; scientometrics; Author Keywords; Keywords Plus (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219525924500061

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