文章基本信息

标题：How Can People Express Their Trait Self-Esteem Through Their Faces in 3D Space?
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作者：Wang, Xiaoyang ; Liu, Xiaoqian ; Wang, Yuqian 等
期刊名称：Frontiers in Psychology
电子版ISSN：1664-1078
出版年度：2021
卷号：12
页码：8
DOI：10.3389/fpsyg.2021.591682
出版社：Frontiers Media
摘要：Background: Trait self-esteem reflects stable self-evaluation, and it affects social interaction patterns. But whether and how trait self-esteem can be expressed through behaviours are controversial. Considering that facial expressions can effectively convey information related to personal traits, the present study investigated the 3D (three-dimensional) facial movements related to self-esteem level, and the sex differences therein. Method: The sample comprised 238 participants (46.2% males, 53.8% females). Their levels of trait self-esteem were evaluated by employing the Rosenberg Self-Esteem Scale (SES) (47.9% low self-esteem, 52.1% high self-esteem). During self-introductions, their facial movements in 3D space were recorded by Microsoft Kinect. Two-way ANOVA was performed to analyse the effect of self-esteem and gender on 3D facial movements. Additionally, Logistic regression models were established to describe the relationship between 3D facial movements and self-esteem levels in both genders. Results: The results of two-way ANOVA revealed a main effect of trait self-esteem level for cheeks and lips’ movements. Meanwhile, there was significant interaction between trait self-esteem and gender on the variability of lips’ movements. In addition, the combination of facial movements can effectively identify trait self-esteem in men and women, with 75.5% and 68% accuracy respectively. Conclusion: The present results suggest that the 3D facial expressions of individuals with different trait self-esteem levels were different, and such difference is affected by gender. Our study explores a possible way in which trait self-esteem plays a role in social interaction, and also provide the basis for automatic self-esteem recognition.
关键词：facial expressions; Three-dimensional data; gender; Logistic regression; Trait self-esteem; Two-way ANOVA