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From reductionism to complex systems: Paradigm shift and knowledge evolution in competitive sports research using
1School of Physical Education, Shanghai University of Sport, Shanghai, China.
Plos One
|March 30, 2026
Summary
This study uses natural language processing (NLP) to map competitive sports research, revealing a shift towards holistic well-being and integrated technologies. Key areas include sports injury, mental health, and event management evolution.
Area of Science:
- Sports Science
- Bibliometrics
- Natural Language Processing (NLP)
Background:
- Traditional bibliometric methods struggle with the complexity of competitive sports research.
- Exponential growth in research volume necessitates advanced analytical approaches.
- A micro-semantic perspective is needed to understand the field's structure and evolution.
Purpose of the Study:
- To reconstruct the knowledge structure of competitive sports research using NLP.
- To analyze the evolutionary dynamics of the field from a micro-semantic viewpoint.
- To identify emerging trends and paradigm shifts in sports science.
Main Methods:
- Utilized BERTopic topic modeling and dynamic regression analysis.
- Performed unstructured text mining on 24,659 core abstracts (2010-2024).
- Data sourced from Web of Science, PubMed, and Scopus databases.
Main Results:
- Identified a
- monocentric, multi-dimensional
- hierarchical knowledge structure.
- Topic 0 ('Sports Injury and Load Management') shows continuous growth, forming the field's foundation.
- Topic 1 ('Sports Mental Health') exhibits explosive growth, indicating a paradigm shift to holistic well-being.
- Topic 4 ('Mega-event Management') shows saturation; research evolved through Budding, Rapid Development, and Multi-dimensional Transition periods.
Conclusions:
- Competitive sports science is transitioning from reductionism to a complex systems perspective.
- Future research will likely integrate biomedical technologies with humanistic psychology.
- This study offers a novel methodological approach to understanding scientific discipline evolution.
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