A Statistical Model of Facial Attractiveness
A Statistical Model of Facial Attractiveness
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DOI：
10.1177/0956797611419169
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发表时间：
2011-09-01
影响因子：
8.2
通讯作者：
Todorov, Alexander
中科院分区：
文献类型：
--
作者：
Said, Christopher P.;Todorov, Alexander
此前的研究发现，面部平均和性别差异是影响面部吸引力的重要因素。平均性和性别两面性的描述为理解面孔的吸引力提供了重要的第一步，应该因为面孔的简朴而受到重视。然而，我们发现，它们对面部吸引力的差异解释相对较少，特别是对男性面部。作为这些描述的替代，我们建立了一个回归模型，该模型将吸引力定义为面孔在多维面孔空间中位置的函数。该模型提供了比平均性和性别二型性解释更强的预测力，并揭示了以前没有报道的吸引力成分。该模型表明，平均在某些方面具有吸引力，但在其他方面不具有吸引力，并解决了之前关于性别二态对男性面孔吸引力的影响的相互矛盾的报道。
Previous research has identified facial averageness and sexual dimorphism as important factors in facial attractiveness. The averageness and sexual dimorphism accounts provide important first steps in understanding what makes faces attractive, and should be valued for their parsimony. However, we show that they explain relatively little of the variance in facial attractiveness, particularly for male faces. As an alternative to these accounts, we built a regression model that defines attractiveness as a function of a face's position in a multidimensional face space. The model provides much more predictive power than the averageness and sexual dimorphism accounts and reveals previously unreported components of attractiveness. The model shows that averageness is attractive in some dimensions but not in others and resolves previous contradictory reports about the effects of sexual dimorphism on the attractiveness of male faces.