认知过程中的惯性:COVID-19疫苗的案例
Joseph Woelfel1, Edward L Fink2, Deborah A Cai2
1Department of Communication, University at Buffalo, SUNY, Buffalo, NY USA.
Quality & quantity
|June 26, 2023
概括
多维缩放模型将人类的态度作为在高维空间中的运动. 这项研究应用了这种方法,以了解有关COVID-19疫苗的态度变化.
科学领域:
- 社会心理学 社会心理学
- 计算语言学 计算语言学
- 网络分析 网络分析
背景情况:
- 人类的认知和文化信仰可以被模拟为在高维非欧几里德空间内的运动.
- 因素分析,多维缩放和利略模型的发展使人类态度的空间建模得到了先进.
- 计算机科学和人工智能的最新进展进一步支持这些复杂的建模技术.
研究的目的:
- 展示多维缩放 (MDS) 的理论和方法贡献.
- 应用MDS来理解与COVID-19疫苗相关的态度变化.
主要方法:
- 使用多维缩放 (MDS) 作为核心分析技术.
- 利用因子分析,利略模型和计算科学的理论框架.
- 应用空间建模来表示复杂的人类态度.
主要成果:
- 多维缩放为分析态度转变提供了一个强大的框架.
- 这项研究说明了空间表示如何阐明疫苗态度动态.
- 展示了MDS在理解复杂的社会现象中的实用性.
结论:
- 多维缩放为态度研究提供了重要的理论和方法价值.
- 将MDS应用于COVID-19疫苗态度提供了新的见解.
- 态度的空间建模是社会科学研究的一个强大的工具.
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