From likely to likable: The role of statistical typicality in human social assessment of faces
From likely to likable: The role of statistical typicality in human social assessment of faces
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从可能到讨人喜欢：统计典型性在人类社会面孔评估中的作用
DOI：
10.1073/pnas.1912343117
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Angela J. Yu
中科院分区：
文献类型：
--
作者：
C. Ryali;Stanny Goffin;P. Winkielman;Angela J. Yu
人类很容易从陌生人的面部特征中形成社交印象，比如吸引力和可信度。了解这些印象的来源具有明显的科学意义和社会意义。根据大脑表征的有效编码假设，以及克劳德·香农的理论结果，最有效的表征系统将较短的代码分配给统计上更典型的数据(量化为对数似然)，我们认为，社会对面孔的喜欢随着统计典型性的增加而增加。结合人类行为数据和计算模型，我们发现人脸图像的感知吸引力、可信性、优势度和效价随着其统计典型性(对数似然)线性增加。我们还发现，统计典型性至少可以部分解释对称性在吸引力感知中的作用。此外，通过假设大脑关注与任务相关的面部特征子集，并使用这些特征评估面孔的对数可能性，我们的模型可以解释社会心理学中发现的“平均丑”效应，即在分类任务中，其他有吸引力的类别间面孔的吸引力会降低。
Humans readily form social impressions, such as attractiveness and trustworthiness, from a stranger’s facial features. Understanding the provenance of these impressions has clear scientific importance and societal implications. Motivated by the efficient coding hypothesis of brain representation, as well as Claude Shannon’s theoretical result that maximally efficient representational systems assign shorter codes to statistically more typical data (quantified as log likelihood), we suggest that social “liking” of faces increases with statistical typicality. Combining human behavioral data and computational modeling, we show that perceived attractiveness, trustworthiness, dominance, and valence of a face image linearly increase with its statistical typicality (log likelihood). We also show that statistical typicality can at least partially explain the role of symmetry in attractiveness perception. Additionally, by assuming that the brain focuses on a task-relevant subset of facial features and assessing log likelihood of a face using those features, our model can explain the “ugliness-in-averageness” effect found in social psychology, whereby otherwise attractive, intercategory faces diminish in attractiveness during a categorization task.
影响因子：
5.4
作者：
Ma, Debbie S.;Correll, Joshua;Wittenbrink, Bernd
通讯作者：
Wittenbrink, Bernd
当分类不确定时预测自然类别成员的特征。
DOI：
10.1037//0278-7393.21.3.646
发表时间：
1995
期刊：
Journal of experimental psychology. Learning, memory, and cognition
影响因子：
--
作者：
Malt,BC;Ross,BH;Murphy,GL
通讯作者：
Murphy,GL