ARC Centre of Excellence in Cognition and Its Disorders & School of Psychology, University of Western Australia, Perth, Western Australia, Australia.
PLoS One. 2011;6(11):e26653. doi: 10.1371/journal.pone.0026653. Epub 2011 Nov 11.
Most of what we know about what makes a face attractive and why we have the preferences we do is based on attractiveness ratings of static images of faces, usually photographs. However, several reports that such ratings fail to correlate significantly with ratings made to dynamic video clips, which provide richer samples of appearance, challenge the validity of this literature. Here, we tested the validity of attractiveness ratings made to static images, using a substantial sample of male faces. We found that these ratings agreed very strongly with ratings made to videos of these men, despite the presence of much more information in the videos (multiple views, neutral and smiling expressions and speech-related movements). Not surprisingly, given this high agreement, the components of video-attractiveness were also very similar to those reported previously for static-attractiveness. Specifically, averageness, symmetry and masculinity were all significant components of attractiveness rated from videos. Finally, regression analyses yielded very similar effects of attractiveness on success in obtaining sexual partners, whether attractiveness was rated from videos or static images. These results validate the widespread use of attractiveness ratings made to static images in evolutionary and social psychological research. We speculate that this validity may stem from our tendency to make rapid and robust judgements of attractiveness.
我们对于什么使一张脸具有吸引力以及我们为什么有这样的偏好的了解大多基于对人脸静态图像（通常是照片）的吸引力评分。然而，有几项报告表明，这些评分与对动态视频剪辑的评分没有显著相关性，这就对该文献的有效性提出了挑战。在这里，我们使用大量男性面孔样本测试了对静态图像进行吸引力评分的有效性。我们发现，尽管视频中提供了更多的信息（多个视角、中性和微笑的表情以及与言语相关的动作），但这些评分与对这些男性的视频评分非常吻合。不出所料，鉴于这种高度一致性，视频吸引力的组成部分与之前报告的静态吸引力的组成部分也非常相似。具体来说，平均性、对称性和男性气质都是从视频中评定的吸引力的重要组成部分。最后，回归分析得出了非常相似的效果，即吸引力对获得性伴侣的成功的影响，无论吸引力是从视频还是静态图像中评定的。这些结果验证了在进化和社会心理学研究中广泛使用对静态图像进行的吸引力评分。我们推测，这种有效性可能源于我们对吸引力进行快速而有力判断的倾向。
