学生自治网络的基于网络的分析以及公民参与结果中的预测作用
Jing Liu1, Putu Kerti Nitiasih2, Made Hery Santosa2
1College of Education, Universitas Pendidikan Ganesha, Jalan Udayana, Bali Province, 81116, Indonesia. Jing.Liu1995@outlook.com.
Scientific reports
|January 27, 2026
概括
学生治理网络显著影响公民参与. 网络位置,特别是中央连接,增强了参与度,机器学习模型准确地预测了参与度.
科学领域:
- 社会科学 社会科学 社会科学
- 网络科学 网络科学
- 政治科学 政治科学是指政治学.
背景情况:
- 学生治理网络 (SGN) 对于发展公民技能至关重要.
- 了解公民参与成果 (CPO) 的结构性决定因素至关重要.
研究的目的:
- 分析SGN结构和CPO之间的关系.
- 确定促进更大的公民参与的网络位置.
主要方法:
- 社会网络分析 (SNA) 基于237名学生参与者的数据.
- 多变量回归 (MR) 和机器学习 (ML) 分类 (XGBoost).
主要成果:
- SGNs具有模块化,分层结构,具有中央枢纽.
- 网络位置,特别是自身向量中心性和社区E-I指数,显著预测CPO.
- 在区分参与的学生方面,ML模型实现了高精度 (0.781) 和AUC-ROC (0.842).
结论:
- 治理的公民利益根据网络位置分布不均.
- 中心地位和跨社区联系增强了公民参与.
- 调查结果为治理设计和公民教育策略提供了信息.
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