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This study chooses Chinese athletes as the research object and constructs the overall network of its social support network and discussion network. From the micro-, meso-, and macrolevels of the social network structure, the structure and characteristics of the athlete’s overall social network are analyzed. Through research, we found that there is embeddedness, that is, the relevance, between society support networks, between society discussion networks, and between society support networks and society discussion networks. At the same time, in the athletes’ (...) social support network and social discussion network, some athletes have no contact with other players; they have no “power” in the group as well, so it is difficult to obtain network resources. We also found that there are small-world characteristics in the social network of Chinese professional athletes. The above findings will provide a deeper understanding of the peculiarities of athlete groups and have certain practical significance for improving athletes’ daily training and life management conditions. (shrink)

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This study evaluated the dimensionality and psychometric properties of the Brief Self-Control Scale (BSCS) using a sample of university students in mainland China. Nine hundred and three students from a Chinese university participated in this study. The internal consistency, criterion validity, factorial validity and construct validity of the scale were examined. The Chinese versions of the BSCS demonstrated good internal consistency. The BSCS also showed significant moderate correlations with other construct-related scales. Exploratory factor analysis and confirmatory factor analysis suggested that (...) only a modified 11-item BSCS with a four-factor structure was a good model fit in the sample of Chinese university students. The implications for research and theoretical development are discussed. (shrink)

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In this study, we sorted out the research hotspots in sports science by bibliometric method and also used social network analysis to explore the relationship between knowledge networks and their scientific performance. We found 38 high-frequency keywords with obvious curricular nature or classical direction of sports science research and 4 high-frequency research groups. The topics of hotspots covered the secondary disciplines of sports science: physical education and training, national traditional sports, sports human science, and sports humanities and sociology. However, sports (...) human science research is less; therefore, accelerating the research of sports human science is the focus of future research. Meanwhile, we use social network structure analysis to study the relationship between knowledge elements in knowledge networks and their scientific performance. In addition to betweenness centrality, the closeness centrality, clustering coefficient, and structural holes of knowledge elements are significantly and positively related to their influence. In the relationship between knowledge elements and productivity, betweenness centrality and closeness centrality show significant positive correlations, and clustering coefficient and structural hole show significant negative correlations. Therefore, knowledge networks can be used to predict the scientific performance of knowledge elements. (shrink)

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Social network theory is an important paradigm of social structure research, which has been widely used in various fields of research. This paper reviews the development process and the latest progress of social network theory research and analyzes the research application of social network. In order to reveal the deep social structure, this paper analyzes the structure of social networks from three levels: microlevel, mesolevel, and macrolevel and reveals the origin, development, perfection, and latest achievements of complex network models. The (...) regular graph model, P1 model, P2 model, exponential random graph model, small-world network model, and scale-free network model are introduced. In the end, the research on the social network structure is reviewed, and social support network and social discussion network are introduced, which are two important contents of social network research. At present, the research on social networks has been widely used in coauthor networks, citation networks, mobile social networks, enterprise knowledge management, and individual happiness, but there are few research studies on multilevel structure, dynamic research, complex network research, whole network research, and discussion network research. This provides space for future research on social networks. (shrink)

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