测量宪法偏好:一种分析公众咨询数据的新方法
Andrés Cruz1, Zachary Elkins1, Roy Gardner2
1Department of Government, University of Texas at Austin, Austin, Texas, United States of America.
PloS one
|December 14, 2023
概括
分析宪法设计的公众咨询数据是一项挑战. 本研究引入了一种新的自然语言处理方法,用于对宪法主题的公民反进行分类,从而实现全球比较.
科学领域:
- 政治科学 政治科学是指政治学.
- 计算社会科学 计算社会科学
- 宪法 宪法 宪法 宪法 宪法
背景情况:
- 公共商对于宪法设计至关重要,但产生了大量的非结构化数据集.
- 分析这些叙事数据的现有方法有限,缺乏标准化.
- 比较宪法项目 (CCP) 为宪法主题提供了一个参考本体学.
研究的目的:
- 开发和验证一种新的方法来分析关于宪法问题的公众咨询数据.
- 将公众商中的公民关切与全球宪法中存在的主题进行比较.
- 解决从宪法设计过程中分析大量叙事数据的实际挑战.
主要方法:
- 使用了来自比较宪法项目 (CCP) 的综合参考本体.
- 应用自然语言处理 (NLP),特别是句子级语义相似性,以分类查询响应.
- 分析了来自智利2016年公众商的大量数据集 (265,000个响应).
主要成果:
- 通过NLP,成功地根据宪法主题对公民的反应进行了分类.
- 能够比较公民优先考虑的议题和现有全球宪法中的议题.
- 证明了从公众咨询中分析大规模叙事数据的可行性.
结论:
- 开发的方法提供了一个可扩展和标准化的方法来分析公众咨询数据.
- 这种技术可以揭示公民在宪法设计中的优先事项,并促进跨国比较.
- 这种方法对参与公众参与的研究人员,政策制定者和宪法起草者产生了重大影响.
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