Historical Patterns, Evolution of Models, and Future Perspectives of Interdisciplinary Collaboration an Empirical Study Based on Global Scientific Literature Data from 1950 to 2020
Interdisciplinary research is a driving force for the development of new productive forces. Based on 82.6 million scientific papers published between 1950 and 2022, this study analyzes different combinations of disciplines across 27 fields, revealing the development trends and characteristics of interdisciplinary collaborative research through three key dimensions: the degree of collaboration, team size, and research impact. Notably, the study emphasizes the evolving cooperative relationships among authors and how this collaboration dynamic influences interdisciplinary research. It identifies four modes of interdisciplinary collaboration: Emerging and Hot Topics, Structured Hierarchy, Relatively Close Discipline, and Large Project. Further research indicates that Large Project began to emerge after 2010. Additionally, a notable shift in collaboration modes can be observed between 2010 and 2020, transitioning from Emerging and Hot Topics to Structured Hierarchy. Furthermore, this study attempts to analyze the driving factors behind this shift from the perspective of research topics. The findings contribute to understanding the evolution of interdisciplinary collaboration and its driving factors, exploring new interdisciplinary collaboration models, and promoting organized scientific cooperation.
Authors
- Xiaoming Fu (ORCID: https://orcid.org/0000-0002-8012-4753)
- Boen Liu (ORCID: https://orcid.org/0009-0000-7134-7595)
- Jingjing Qu (ORCID: https://orcid.org/0000-0002-8510-433X)
- Kunpeng Xu (ORCID: https://orcid.org/0000-0003-0977-1955)
- Hui Zou (ORCID: https://orcid.org/0009-0006-3361-0691)
- Liwei Chen (ORCID: https://orcid.org/0000-0001-7025-1380)
Institutions
- Shanghai University (CN)
- Fudan University (CN)
- Shanghai Library (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Duke Kunshan University (CN)
- Shanghai Artificial Intelligence Laboratory (CN)
- University of Göttingen (DE)
Publication Details
- Published
- 2024-10-24
- DOI
- https://doi.org/10.1145/3698387.3699996
- Citations
- 1
- Primary Topic
- scientometrics and bibliometrics research
- Type
- article
- Field-Weighted Citation Impact
- 0.46