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Home Exclusive Cognitive Science

Machine learning study identifies facial features that are central to first impressions

by Beth Ellwood
October 21, 2021
Reading Time: 4 mins read
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A study published in Social Psychological and Personality Science presents evidence that people make judgments about strangers’ personalities based on how closely their resting faces resemble emotional expressions. It was found that among seven classes of facial characteristics, resemblance to emotional expressions was the strongest predictor of impressions of both trustworthiness and dominance.

It has long been demonstrated that people form rapid impressions of others based on their physical appearances. Such quick judgments can have strong repercussions — for example, when juries are forming impressions of the accused during criminal trials or when hiring managers are screening potential candidates.

“One thing I find fascinating about first impressions is how quickly and intuitively they come to mind. For example, I might see a stranger on the train and immediately get the feeling that they cannot be trusted. I want to understand where these intuitions come from. What is it about a person’s appearance that makes them appear untrustworthy, intelligent, or dominant to us?” said study author Bastian Jaeger, an assistant professor at the Vrije Universiteit Amsterdam.

While many studies have identified specific facial characteristics that are associated with personality impressions, Jaeger and his colleague Alex L. Jones note that this type of research comes with its challenges. Since many facial features are correlated, it is tricky to identify the unique effects of a given characteristic. For example, if a face is manipulated to look more like it is smiling, these adjustments will also influence the “babyfacedness” of the face. For this reason, Jaeger and Jones set out to examine the relative predictive value of a given facial characteristic for personality impressions, by examining a wide range of facial features at once.

The researchers analyzed a dataset from the Chicago Face Database, which included 597 faces of individuals maintaining a neutral expression in front of a plain background. The dataset had previously been presented to a sample of 1,087 raters who each rated a subset of 10 faces on a wide range of characteristics. These characteristics included attractiveness, unusualness, babyfacedness, dominance, and trustworthiness of the face. The sample also rated the extent that faces resembled six emotional expressions — happiness, sadness, anger, disgust, fear, and surprise.

In total, the database included information on 28 facial features which the researchers divided into seven categories: demographics, morphological features, facial width-to-height ratio (fWHR), perceived attractiveness, perceived unusualness, perceived babyfacedness, and emotion resemblance.

Using machine learning, Jaeger and Jones tested the predictive value of each of these classes of facial features for impressions of trustworthiness and dominance. It was found that resemblance to emotional expressions was the best predictor for perceptions of both trustworthiness and dominance. Emotion resemblance also explained the most variance in perceptions of trustworthiness and dominance out of all seven classes.

Next, using regression analysis, the researchers examined the relative predictive value of each of the 28 facial features. Here, they found that resemblance to a happy expression was the strongest predictor of trustworthiness. Attractiveness and being Asian were also substantial positive predictors, and resemblance to an angry expression was a fairly strong negative predictor. For perceptions of dominance, resemblance to an angry expression was the strongest positive predictor, and being female was the strongest negative predictor. Contrary to previous findings, fWHR was not a strong predictor of either trustworthiness or dominance perceptions.

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The study’s authors say this pattern of findings is in line with a phenomenon called emotion overgeneralization, which posits that people are especially sensitive to reading emotions in other people’s faces since emotions convey highly relevant social information. Because of this oversensitivity, people end up detecting emotions even in neutral faces that “structurally resemble emotional expressions.” This information is then used to infer personality characteristics from the face, such as trustworthiness.

“We shouldn’t be too confident in our first impressions,” Jaeger told PsyPost. “They might come to mind easily and effortlessly, but not because we are so good at judging others. Rather, it seems like our oversensitive emotion detection system makes us ‘see things’ in others’ faces. Even when a person is not sending any emotional signals, we might detect a smile, just because the corners of their mouth are slightly tilted upwards. And because of our tendency to overgeneralize from emotional states to psychological traits, we not only think that they are happy right now, but that they are happy, outgoing, and trustworthy in general.”

Notably, the results imply that there are additional features that relate to impression formation that the study did not test for. “Emotion resemblances explained 53% and 42% of the variance in trustworthiness and dominance perceptions,” Jaeger and Jones report. “Even the optimized Elastic Net models explained around 68% of the variance, indicating there are other important factors contributing to personality impressions.” Future studies should attempt to uncover more predictors and shed additional light on the relative importance of specific facial features.

“Our findings are based on relatively large and demographically diverse samples of raters and targets, but they were all from the United States,” Jaeger noted. “It’s important to test the generalizability of our results. We find that first impressions are largely based on how much a person’s facial features resemble a smile or a frown, but is that also true for people in China, Chile, or Chad?”

The study, “Which Facial Features Are Central in Impression Formation?”, was authored by Bastian Jaeger and Alex L. Jones.

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