通过人机协作加强网络欺凌的社会科学研究
Andrea Baños-Ramos1, María Reneses1,2, Jaime Pérez3
1Institute for Research in Technology (IIT), ICAI Engineering School, Universidad Pontificia Comillas, 28015, Madrid, Spain.
Scientific reports
|September 26, 2025
概括
网络欺凌 (CB) 是青少年日益关注的问题. 本研究介绍了一个人机框架,使用因果发现和贝叶斯网络来理解CB CB.
科学领域:
- 社会科学 社会科学 社会科学
- 计算机科学 计算机科学
- 青少年心理学 青少年心理学
背景情况:
- 网络欺凌 (CB) 影响了近一半的欧洲儿童,由于数字匿名性,这构成了重大挑战.
- 由于依赖于相关性,传统的统计方法难以确定CB中的因果关系.
- 伦理限制阻止了对网络欺凌的实验研究,需要先进的分析方法.
研究的目的:
- 引入一个新的人机共识框架,用于网络欺凌研究中的因果发现.
- 支持社会科学家了解网络欺凌背后的复杂因果机制.
- 利用数据驱动的因果推断和专家知识进行可靠的分析.
主要方法:
- 使用定向环形图 (DAG) 来从观测数据中确定因果关系.
- 将自动因果发现算法与专家知识相结合,以减轻每个方法的局限性.
- 采用概率图形因果模型 (PGCM) 或贝叶斯网络,以提高解释性和概率推理.
主要成果:
- 拟议的框架允许混合方法结合算法和专家驱动的见解.
- 它促进了对因果关系效应的模型集合估计的创建.
- 这种方法减轻了认知偏见,提高了模型构建的透明度.
结论:
- 人机共识框架为网络欺凌研究中的因果发现提供了一个强大的工具.
- 可解释,专家知情的因果模型对于指导在伦理限制的研究领域的政策和干预策略至关重要.
- 这种方法提升了对像网络欺凌这样复杂的社会现象的理解.
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