How Can People Express Their Trait Self-Esteem Through Their Faces in 3D Space?

Abstract

BackgroundTrait self-esteem reflects stable self-evaluation, and it affects social interaction patterns. However, whether and how trait self-esteem can be expressed through behaviors are controversial. Considering that facial expressions can effectively convey information related to personal traits, the present study investigated the three-dimensional (3D) facial movements related to self-esteem level and the sex differences therein.MethodsThe 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 analyze 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.ResultsThe results of two-way ANOVA revealed a main effect of trait self-esteem level for cheeks and lips’ movements. Meanwhile, there was a 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.ConclusionThe 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 provides the basis for automatic self-esteem recognition.

Ecological recognition of self-esteem leveraged by video-based gait

“…This study not only supports prior research that showed behavior markers might be used to assess self-esteem and demonstrates that gait patterns can reflect self-esteem rather effectively, but it also represents a considerable advance in comparison to earlier studies ( 14 , 16 ). More significantly, the use of an omnipresent camera enables the implementation of a real-time, population-based prediction of human psychological traits (self-esteem) scores.…”

“…More importantly, using feature selection with a theoretical foundation improves the explanation of the findings. Last but not least, we significantly expanded the sample size, which improved the reliability of the findings ( 16 , 31 ).…”

“…To the best of our knowledge, only sporadic research carried out to testify the validation of behavioral assessment. In addition to the research mentioned above ( 14 ), Wang and his colleagues employed Kinect to record participants’ facial expressions during self-introduction to predict participants’ self-esteem using machine learning models ( 16 ). The two studies share the same issue in that all of their findings are based on 3D data captured by the Kinect, however, in the real world outside of laboratories, the behavior recording instruments are generally 2D such as the surveillance equipment or video cameras in a public place.…”

Questionnaires based on natural language processing elicit immersive ruminative thinking in ruminators: Evidence from behavioral responses and EEG data

“…While RRS has been widely employed in ruminative research, the limitations of this scale are also significant, especially regarding the presence of psychological selection (Wang et al, 2020 ; Miao et al, 2021 ). Camouflage, falsification, social approval, and other issues (Dunning et al, 2005 ; Schwarz, 2012 ; Wang et al, 2020 , 2021 ) have greatly affected the acceptance and validity of rumination-related psychological testing. Therefore, further advancements are necessary in inducing ruminative conscious activity accurately, measuring the associated brain activity objectively, and exploring the neural biomarkers of rumination to identify ruminators and predict future rumination for precise psychological selection.…”