集体记忆和流性任务:利用网络分析来更丰富地理解集体认知
Garrett D Greeley1, Tori Peña1, Nicholas W Pepe1
1Department of Psychology, Stony Brook University.
概括
集体记忆,群体的共同回忆,显示出了显著的稳定性. 对回忆数据的网络分析揭示了人们所记忆的东西和他们回忆的顺序的一致模式.
科学领域:
- 认知心理学 认知心理学
- 社会心理学 社会心理学
- 网络科学 网络科学
背景情况:
- 集体记忆研究经常使用流性任务来研究共享的回忆.
- 网络分析在语义记忆研究等相关领域已经被证明是有价值的.
- 网络视角为深入了解集体认知提供了潜在的潜力.
研究的目的:
- 调查网络科学工具是否可以增强对集体记忆的研究.
- 为了分析长达十年的美国城市集体记忆回忆数据集.
- 检查被召回内容的稳定性和随时间推移的召回顺序.
主要方法:
- 综述集体记忆和语义记忆文学.
- 对一个大型的纵向流动性数据集的描述性和网络分析.
- 检查召回频率,输出位置和召回项目之间的过渡率.
主要成果:
- 某些美国城市在不同的时间和背景下以一致的频率和相似的输出位置被召回.
- 网络分析表明,被召回城市之间的过渡率稳定.
- 集体召回的内容和顺序都表现出显著的稳定性.
结论:
- 网络科学为分析集体记忆提供了宝贵的工具.
- 美国城市的集体记忆在内容和回忆顺序上都表现出惊人的稳定性.
- 这种稳定性提供了对共享记忆的基础结构的洞察.
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