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非操作性判断中的离散,反复和可扩展的模式是情感图片评级的基础
Leandros Stefanopoulos1,2, Byoung-Woo Kim3, John Sheppard4
1Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA.
Cognitive processing
|December 7, 2024
概括
与操作任务不同,非操作人员的图像评级任务可以快速且负担得起地量化人类偏好的合法性. 该方法为全球适用的偏好评估提供了一个简单,可扩展的框架.
科学领域:
- 行为经济学是一种行为经济学.
- 心理物理学的精神物理.
- 量化心理学 量化心理学
背景情况:
- 在一个强化奖励框架中的操作按键任务展示了合法的人类偏好行为,类似于"想要".
- 这些任务需要大量的时间 (20-40分钟) 并不容易应用于无监督的互联网研究.
- 与"喜欢"类似的非操作员评级任务的合法性仍然没有研究.
研究的目的:
- 调查非操作任务的图片评级任务是否与操作任务具有类似的法律关系.
- 评估使用简单,简短和无监督的评级任务进行偏好评估的可行性.
- 建立一个容易部署的人类偏好的定量框架.
主要方法:
- 利用了来自三个独立的人口队列 (N=501,506,4019) 的非操作图像评级数据.
- 采用7点的利克特级别来对图像进行偏好评分,这些图像来自国际情感图像系统.
- 计算位置,分散和变量来导出值,极限和权衡函数.
主要成果:
- 非操作的图像评级产生了类似于操作任务的值,极限和权衡函数,单个R2>0.80.
- 单个函数的数学公式是离散的,反复的,在队列中一致的.
- 诸如风险厌恶之类的行为特征在所有队列中也是一致的,支持评级建模中的合法性.
结论:
- 非操作任务的图片评分任务显示了人类偏好的合法关系,类似于操作任务.
- 该方法为定量偏好评估提供了一个简单,快速,低成本和可扩展的框架.
- 该框架可在任何数字设备上部署,促进全球互联网研究.
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