What Facial Appearance Reveals Over Time: When Perceived Expressions in Neutral Faces Reveal Stable Emotion Dispositions

Abstract

It might seem a reasonable assumption that when we are not actively using our faces to express ourselves (i.e., when we display nonexpressive, or neutral faces), those around us will not be able to read our emotions. Herein, using a variety of expression-related ratings, we examined whether age-related changes in the face can accurately reveal one’s innermost affective dispositions. In each study, we found that expressive ratings of neutral facial displays predicted self-reported positive/negative dispositional affect, but only for elderly women, and only for positive affect. These findings meaningfully replicate and extend earlier work examining age-related emotion cues in the face of elderly women (Malatesta et al., 1987a). We discuss these findings in light of evidence that women are expected to, and do, smile more than men, and that the quality of their smiles predicts their life satisfaction. Although ratings of old male faces did not significantly predict self-reported affective dispositions, the trend was similar to that found for old female faces. A plausible explanation for this gender difference is that in the process of attenuating emotional expressions over their lifetimes, old men reveal less evidence of their total emotional experiences in their faces than do old women.

Effects of Robot Facial Characteristics and Gender in Persuasive Human-Robot Interaction

“…Finally, the facial emotional expression of the participants while interacting with the advisor were captured and analyzed using a software called FaceReader Adams et al, 2016) which is based on Facial Action Coding System (FACS) (Ekman and Friesen, 1978). We counted the instances where FaceReader would classify a facial expression as angry to obtain a behavioral measure of reactance.…”

Everyday Beliefs About Emotion Perceptually Derived From Neutral Facial Appearance

“…The present studies extend these insights to better understand lay beliefs about older and younger adults' emotion dispositions and their impact on behavioral outcomes. In Study 1, we found that older versus younger faces objectively have more negative emotion-resembling cues in the face (using computer vision), and that raters likewise attribute more negative emotional dispositions to older versus younger adults based just on neutral facial appearance (see too Adams et al, 2016). In Study 2, we found that people appear to encode these negative emotional appearance cues in memory more so for older than younger adult faces.…”

“…FaceReader TM is a commercial computer vision tool used to objectively analyze the presence of expressions, action units, and emotional overall valence in facial images. FaceReader TM is well established and validated in the scientific literature, with results approaching expert level (Lewinski, 2015;Adams et al, 2016).…”

“…Participants (N = 49; 39 females, 10 males, M age = 19.2) were college students. Stimuli were 888 older and younger adult neutral faces from the FACES image set (Ebner et al, 2010), the Face Database (Minear and Park, 2004), and the Humboldt image set (see, Adams et al, 2016) for a total of 394 old female adults, 209 old male adults, 144 young female adults, and 141 young male adults.…”

“…For example, male faces (versus female faces) tend to structurally resemble anger expressions with lowered brows, thin lips, and square jaws, whereas female faces structurally resemble happy faces, in line with prevailing gender emotion stereotypes (see Adams et al, 2015 for review;Hess et al, 2004;Becker et al, 2007;Zebrowitz et al, 2010;Palumbo et al, 2017). Further, as a face ages, it takes on more emotionresembling cues (Malatesta et al, 1987;Adams et al, 2016), which have been argued to contribute to negative age-related stereotypes (Hess et al, 2012).…”