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大学生社会网络结构对其运动动机内化的非线性影响机制：基于图神经网络的实证研究
The Nonlinear Influence Mechanism of College Students’ Social Network Structure on Their Exercise Motivation Internalization: An Empirical Study Based on Graph Neural Networks
目的：探究大学生在社会网络中的位置特征如何影响其运动动机的内化机制，以揭示社会网络结构对运动动机的深层影响。方法：运用社会网络分析法对384名大学生进行调查，通过《社会网络问卷》构建人际网络，结合《运动动机量表》评估运动动机类型。运用相关软件计算社会网络中心性指标，通过分段回归分析和图卷积神经网络识别非线性关系。结果：内部动机型大学生的社会网络中介中心度（M=0.68）显著高于无动机型大学生（M=0.43），并且差异显著（F=116.43，p<0.001）。这意味着内部动机型大学生在班级中更多地发挥桥梁的作用，联系着不同的社交圈。中介中心度是预测运动动机的最强因子（β=0.39，p<0.001），当其超过约0.60的临界值后，中介中心度对个体运动动机的积极影响呈现增大趋势。最终的图卷积网络模型能解释运动动机59%的变异（R2=0.59）。结论：个体在社会网络中的桥梁位置通过增强其对信息和资源的控制力，满足其自主性和胜任感的心理需求，进而促进其运动动机内化。该结论揭示了通过改变大学生的社会网络结构可以促进其运动参与的理论与实践路径，为精准干预提供了新视角。
Purpose: To investigate how college students’positional characteristics in social networks influence the internalization of their exercise motivation, and to reveal the deep mechanism through which social network structure affects motivation formation. Methods: A social network analysis approach was used to survey 384 college students. Interpersonal networkswere constructed using the Social Relationship Questionnaire, and the Sport Motivation Scale (SMS) was simultaneously administered to assess motivation types. UCINET 6.0 was used to calculate network centrality indexes, and segmented regression analysis and graph convolutional neural networks were used to identify nonlinear relationships. Results: The network betweenness centrality of internally motivated students (M=0.68) was significantly higher than that of amotivated students (M=0.43), with a significant difference (F=116.43, p<0.001). This implies that internally motivated students play a more prominent “bridge” role in the class, connecting different social circles. Betweenness centrality was the strongest predictor of exercise motivation (β=0.39, p<0.001), and when it exceeded a critical threshould of approximately 0.60, the positive impact of betweenness centrality on individual exercise motivation exhibited an accelerated growth trend. The final graph convolutional network model explained 59% of the variance in the overall exercise motivation score (R2=0.59). Conclusion: Individuals’ “bridge” position in social networks facilitates the internalization of exercise motivation by increasing their abilities to control information and resources, and satisfying their needs for autonomy and competence. This conclusion reveals the theoretical and practical pathways for improving college students’ participation in sports through optimizing social network structures, providing a new perspective for targeted interventions.
社会网络分析 / 运动动机 / 中介中心度 / 自我决定理论 / 大学生体育
socia lnetwork analysis / exercise motivation / betweenness centrality / self-determination theory / college students’sports
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