Author Multidisciplinarity and Disciplinary Roles in Field of Study Networks

TL;DR

This paper introduces Field of Study networks as a new scientometric tool to analyze multidisciplinary research topics and their roles within scientific communities, demonstrated through case studies on network science and COVID-19 research.

Contribution

It proposes FoS networks for mapping research topics based on author publication patterns, offering an alternative to traditional classification schemes and enabling structural role analysis.

Findings

FoS networks reveal community structures in research topics.

Structural roles highlight key topics and their multidisciplinary importance.

Case studies demonstrate FoS networks' effectiveness in large datasets.

Abstract

When studying large research corpora, "distant reading" methods are vital to understand the topics and trends in the corresponding research space. In particular, given the recognised benefits of multidisciplinary research, it may be important to map schools or communities of diverse research topics, and to understand the multidisciplinary role that topics play within and between these communities. This work proposes Field of Study (FoS) networks as a novel network representation for use in scientometric analysis. We describe the formation of FoS networks, which relate research topics according to the authors who publish in them, from corpora of articles in which fields of study can be identified. FoS networks are particularly useful for the distant reading of large datasets of research papers when analysed through the lens of exploring multidisciplinary science. In an evolving scientific landscape, modular communities in FoS networks offer an alternative categorisation strategy for research topics and sub-disciplines, when compared to traditional prescribed discipline classification schemes. Furthermore, structural role analysis of FoS networks can highlight important characteristics of topics in such communities. To support this, we present two case studies which explore multidisciplinary research in corpora of varying size and scope; namely, 6,323 articles relating to network science research and 4,184,011 articles relating to research on the COVID-19-pandemic.