Abstract

Complex systems science (CSS) and community-based research (CBR) have emerged over the past 50 years as complementary disciplines. However, there is a gap in understanding what has driven the recent proliferation of integrating these two disciplines to study complex and relevant issues. In this review, we report on the results of a scoping review of articles that utilized both disciplines. After two levels of reviewing articles using DistillerSR, a web-based platform designed to streamline and facilitate the process of conducting systematic reviews, we used two forms of natural language processing to extract data. We developed a novel named entity recognition model to extract descriptive information from the corpus of articles. We also conducted dynamic topic modeling to deductively examine in tandem the development of CSS and CBR and to inductively discover the specific topics that may be driving their use in research and practice. We find that among the CSS and CBR papers, CBR topic frequency has grown at a faster pace than CSS, with CBR using CSS concepts and techniques more often. Four topics that may be driving this trend are collaboration within social systems, business management, food and land use and knowledge, and water shed management. We conclude by discussing the implications of this work for researchers and practitioners who are interested in studying and solving complex social, economic, and health-related issues.

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