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Emotional Expressions Reconsidered: Challenges to Inferring Emotion From Human Facial Movements
Open accessAbstract
It is commonly assumed that a person’s emotional state can be readily inferred from his or her facial movements, typically called emotional expressions or facial expressions . This assumption influences legal judgments, policy decisions, national security protocols, and educational practices; guides the diagnosis and treatment of psychiatric illness, as well as the development of commercial applications; and pervades everyday social interactions as well as research in other scientific fields such as artificial intelligence, neuroscience, and computer vision. In this article, we survey examples of this widespread assumption, which we refer to as the common view , and we then examine the scientific evidence that tests this view, focusing on the six most popular emotion categories used by consumers of emotion research: anger, disgust, fear, happiness, sadness, and surprise. The available scientific evidence suggests that people do sometimes smile when happy, frown when sad, scowl when angry, and so on, as proposed by the common view, more than what would be expected by chance. Yet how people communicate anger, disgust, fear, happiness, sadness, and surprise varies substantially across cultures, situations, and even across people within a single situation. Furthermore, similar configurations of facial movements variably express instances of more than one emotion category. In fact, a given configuration of facial movements, such as a scowl, often communicates something other than an emotional state. Scientists agree that facial movements convey a range of information and are important for social communication, emotional or otherwise. But our review suggests an urgent need for research that examines how people actually move their faces to express emotions and other social information in the variety of contexts that make up everyday life, as well as careful study of the mechanisms by which people perceive instances of emotion in one another. We make specific research recommendations that will yield a more valid picture of how people move their faces to express emotions and how they infer emotional meaning from facial movements in situations of everyday life. This research is crucial to provide consumers of emotion research with the translational information they require.
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“Multimodal recognition extends inference to speech prosody, facial movement and physiology, but facial expressions are context-sensitive social cues rather than emotion readouts [29]”
From Caring Without Feeling: Affective Dynamics as the Control Layer of Human-AI Agent Collaboration (2026) · cites this paper as [29]
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“However, our findings allow no conclusions about whether the smiles were “genuine” as expressions of felt joy (Feldman Barrett et al., 2019).”
From Existential threat and responses to emotional displays of ingroup and outgroup members (2023) · cites this paper as Feldman Barrett et al., 2019
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“The notion that discrete emotion categories can be reliably identified by specific behavioural patterns and/or physiological features has been seriously called into doubt by the marked variability within instances of the same category as well as similarities across categories.”
From A new science of emotion: implications for functional neurological disorder (2022) · cites this paper as [57]
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Metadata
- Authors
- Barrett, L. F., Adolphs, R., Marsella, S., Martinez, A. M., & Pollak, S. D.
- Affiliations
- Northeastern University (US)
- California Institute of Technology (US)
- Department of Electrical and Computer Engineering and Center for Cognitive and Brain Sciences, The Ohio State University
- University of Wisconsin–Madison (US)
- Corresponding author
- Barrett, Lisa Feldman
- Venue
- Psychological Science in the Public Interest
- Publisher
- SAGE Publications
- Published
- 2019-07
- Volume
- 20
- Issue
- 1
- Pages
- 1-68
- ISSN
- 1529-1006 (ISSN-L)
- 2160-0031
- PMC
- PMC6640856
- OpenAlex
- W2912483755
- Semantic Scholar
- c489b6787c5af8aca97f4761343a66f3f189b35d
- Cited by
- 1,748
- References
- 444
- Citations by year
- 2026: 238 · 2025: 266 · 2024: 230 · 2023: 302 · 2022: 269 · 2021: 227 · 2020: 186 · 2019: 26
- FWCI
- 102.82
- Type
- journal article
- Language
- en
- Update notices
- correction (2019-11-15)
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Psychological Science in the Public Interest (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Funders
- National Institute of Mental Health (R01MH113234, P50MH094258, R01MH109464, R01MH061285)
- National Eye Institute (R01EY020834)
- National Cancer Institute (U01CA193632)
- National Institute on Deafness and Other Communication Disorders (R01DC014498)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD090256)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Evolutionary Psychology and Human Behavior
- Keywords
- facial expressions, emotion recognition, facial motion, emotion categories, mixed emotions, social communication, emotion perception, anger, disgust, fear, happiness, sadness, surprise
- MeSH terms
- Facial Recognition, Emotions, Facial Expression, Female, Humans, Interpersonal Relations, Judgment, Male, Movement, Psychomotor Performance
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