Quadrant classification and development path of gymnastics-related research topics in Chinese high-quality journals: Based on SCI, PKU Core and CSSCI source journals

Against the macro backdrop of the strategy for developing a strong sporting nation and digital-intelligent transformation, sports organizations have accumulated massive high-value unstructured knowledge assets such as academic literature and reports. Yet their latent strategic value has not been effectively exploited. Converting static knowledge assets into dynamic strategic intelligence represents the central challenge in sports knowledge management.Taking 169 high quality journal papers on gymnastics published from 2016 to 2025 in the China National Knowledge Infrastructure (CNKI, domestic edition) as research objects, this study identifies seven Topics using the Latent Dirichlet Allocation (LDA) model: Topic 1: Technical analysis of bar transitions and choreography in gymnastics competitions; Topic 2: Evolution of the global team structure in men’s artistic gymnastics; Topic 3: Biomechanical analysis of landing techniques among gymnasts; Topic 4: Research on curriculum design and instructional practice in school gymnastics education; Topic 5: Research on balance capability in ‘gymnasts’ apparatus performances; Topic 6: Movement technique analysis of elite gymnasts; Topic 7: Talent cultivation for reserve forces in competitive gymnastics. Quantitative Topic evaluation shows that Topic 4 is a high-concentration and high-coverage Topic; Topic 5 and 6 are high-concentration and low-coverage Topics; Topic 1 is a low-concentration and low-coverage Topic; and Topic 2, 3, and 7 are low-concentration and high-coverage Topics. This study conducts a Topic-based four-quadrant classification diagnosis and proposes differentiated development paths. Accordingly, it identifies future research directions for Topics in each quadrant, including theoretical deepening, application expansion, basic cultivation, and knowledge integration.