日常数字生活的情感动态:打开计算可能性
Maia L Rocklin1, Anna Angelina Garròn Torres1, Byron Reeves2
1Department of Psychology, Stanford University, Stanford, CA 94305 USA.
Affective science
|September 25, 2023
概括
这项研究引入了一种新的AI方法,用于跟踪每天遇到的数字内容的情绪反应. 该方法使用智能手机屏幕截图来绘制个人的情感体验,增强数字福祉研究.
科学领域:
- 心理学 心理学 心理学
- 计算机科学 计算机科学
- 数字福利 数字福利
背景情况:
- 对日常数字刺激对情感影响的理解有限.
- 以前的方法无法从现实世界的数字互动中追踪情绪.
研究的目的:
- 开发和验证人工智能驱动的管道,用于跟踪对数字内容的情感反应.
- 分析日常智能手机使用中的情绪价值和兴奋.
主要方法:
- 在智能手机屏幕截图数据上利用人工智能训练的深度神经网络.
- 从832名成年人中收集了情感价值和兴奋评级,并使用了情感计算模型.
- 从一个新的屏幕截图库与现有的心理研究图像集进行了评分比较.
主要成果:
- 人类参与者对图像的评分与已建立的心理研究样本类似.
- 影响计算模型展示了类似人类的价值和兴奋评级能力.
- 计算管道成功地在规模上绘制了智能手机用户的情感空间.
结论:
- 智能手机截图的AI驱动分析提供了一种可扩展的方法来研究数字情感体验.
- 这种方法可以进行大规模的研究,研究数字内容如何影响每一刻的幸福感.
- 创新的追踪在数字生活中的情感内容为心理学研究开辟了新的途径.
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