数字数据和人格:人类感知和计算机预测的系统审查和元分析
Joanne Hinds1, Adam N Joinson1
1Information, Decisions and Operations Division, School of Management, University of Bath.
Psychological bulletin
|May 16, 2024
概括
这项研究使用数字数据探索了人格预测. 人类感知和机器学习都显示出适度的准确性,但社交媒体和智能手机数据对特征识别产生了负面影响.
科学领域:
- 心理学 心理学 心理学
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
背景情况:
- 越来越多的技术使用产生了大量的数据,促使研究其与人格的联系.
- 从数字数据中对人格预测的发现分散在各个领域,需要合成.
研究的目的:
- 探索人格自我报告与人类感知和机器学习算法的融合有效性.
- 用数字数据评估五大个性特征的识别能力.
- 为了确定不同类型的个性数据的可预测性.
主要方法:
- 研究1:对人类感知研究的五次元分析 (24,124人,30个样本) 评估了趋同有效性.
- 研究2:对计算机预测研究的多层次元分析 (534个效果大小,42个研究) 检查了趋同有效性.
- 多变量分析确定了影响预测准确性的显著调节因素.
主要成果:
- 对人格特征的人类感知 (ρ = 0.380.57) 和机器学习 (ρ = 0.30) 发现了适度的收有效性.
- 社交媒体平台 (X,Facebook,新浪微博),视频和智能手机对预测差异产生了负面影响.
- 五大特征在数据类型中显示了不同程度的可识别性.
结论:
- 结合心理学和计算机科学的跨学科方法可以推进人格理论.
- 了解不同数据源和分析方法的优点和局限性至关重要.
- 未来的研究应该专注于改进从数字足迹预测人格的方法.
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