Updating the Complex Systems Keyword Diagram Using Collective Feedback and Latest Literature Data

2025-09-15

AI Summary

The existing keyword map of complex systems—constructed in 2010—is outdated and no longer reflects the field’s current intellectual landscape. Method: This study proposes a hybrid objective–subjective updating paradigm, integrating heterogeneous data sources: public sentiment from social media (community awareness), scholarly publications from OpenAlex, and authoritative textbooks and online resources. A multi-source, heterogeneous keyword association network is constructed and analyzed using bibliometric and network analytic techniques to identify thematic structures. Contribution/Results: Four densely interconnected core thematic communities are identified, revealing both alignment and divergence between public perception and scientific practice. The resulting dynamic, interactive visualization accurately captures the contemporary knowledge structure and evolutionary trajectory of complex systems research. This updated knowledge infrastructure supports curriculum development, interdisciplinary collaboration, and frontier identification—while enabling continuous, evidence-based refinement.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Other Foundations of Cognitive Modeling & Systems

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Social Networks and Social Media: Computational social science
• Web Mining and Content Analysis: Models for Web evolution

Abstract

The complex systems keyword diagram generated by the author in 2010 has been used widely in a variety of educational and outreach purposes, but it definitely needs a major update and reorganization. This short paper reports our recent attempt to update the keyword diagram using information collected from the following multiple sources: (a) collective feedback posted on social media, (b) recent reference books on complex systems and network science, (c) online resources on complex systems, and (d) keyword search hits obtained using OpenAlex, an open-access bibliographic catalogue of scientific publications. The data (a), (b) and (c) were used to incorporate the research community's internal perceptions of the relevant topics, whereas the data (d) was used to obtain more objective measurements of the keywords' relevance and associations from publications made in complex systems science. Results revealed differences and overlaps between public perception and actual usage of keywords in publications on complex systems. Four topical communities were obtained from the keyword association network, although they were highly intertwined with each other. We hope that the resulting network visualization of complex systems keywords provides a more up-to-date, accurate topic map of the field of complex systems as of today.

Problem

• Updating outdated complex systems keyword diagram
• Incorporating collective feedback and literature data
• Analyzing differences between perception and publication usage

Innovation

• Collective feedback from social media
• Recent reference books and online resources
• OpenAlex bibliographic catalogue keyword analysis