Summary: A new PNAS study challenges the common assumption that human emotions are limited to six universal emotions. Using statistical modeling, researchers have identified 27 distinct categories of human emotion.
Source: UC Berkeley.
New study challenges assumption that most human emotions fall within the categories of happiness, sadness, anger, surprise, fear and disgust.
The Emoji Movie, in which the protagonist can’t help but express a wide variety of emotions instead of the one assigned to him, may have gotten something right.
A new study from the University of California, Berkeley, challenges a long-held assumption in psychology that most human emotions fall within the universal categories of happiness, sadness, anger, surprise, fear and disgust.
Using novel statistical models to analyze the responses of more than 800 men and women to over 2,000 emotionally evocative video clips, UC Berkeley researchers identified 27 distinct categories of emotion and created a multidimensional, interactive map to show how they’re connected.
Their findings are published this week in the early edition of the Proceedings of the National Academy of Sciences journal.
“We found that 27 distinct dimensions, not six, were necessary to account for the way hundreds of people reliably reported feeling in response to each video,” said study senior author Dacher Keltner, a UC Berkeley psychology professor and expert on the science of emotions.
Moreover, in contrast to the notion that each emotional state is an island, the study found that “there are smooth gradients of emotion between, say, awe and peacefulness, horror and sadness, and amusement and adoration,” Keltner said.
“We don’t get finite clusters of emotions in the map because everything is interconnected,” said study lead author Alan Cowen, a doctoral student in neuroscience at UC Berkeley. “Emotional experiences are so much richer and more nuanced than previously thought.”
“Our hope is that our findings will help other scientists and engineers more precisely capture the emotional states that underlie moods, brain activity and expressive signals, leading to improved psychiatric treatments, an understanding of the brain basis of emotion and technology responsive to our emotional needs,” he added.
For the study, a demographically diverse group of 853 men and women went online to view a random sampling of silent 5- to-10-second videos intended to evoke a broad range of emotions.
Themes from the 2,185 video clips — collected from various online sources for the study — included births and babies, weddings and proposals, death and suffering, spiders and snakes, physical pratfalls and risky stunts, sexual acts, natural disasters, wondrous nature and awkward handshakes.
Three separate groups of study participants watched sequences of videos, and, after viewing each clip, completed a reporting task. The first group freely reported their emotional responses to each of 30 video clips.
“Their responses reflected a rich and nuanced array of emotional states, ranging from nostalgia to feeling ‘grossed out,'” Cowen said.
The second group ranked each video according to how strongly it made them feel admiration, adoration, aesthetic appreciation, amusement, anger, anxiety, awe, awkwardness, boredom, calmness, confusion, contempt, craving, disappointment, disgust, empathic pain, entrancement, envy, excitement, fear, guilt, horror, interest, joy, nostalgia, pride, relief, romance, sadness, satisfaction, sexual desire, surprise, sympathy and triumph.
Here, the experimenters found that participants converged on similar responses, with more than half of the viewers reporting the same category of emotion for each video.
The final cohort rated their emotional responses on a scale of 1 to 9 to each of a dozen videos based on such dichotomies as positive versus negative, excitement versus calmness, and dominance versus submissiveness. Researchers were able to predict how participants would score the videos based on how previous participants had assessed the emotions the videos elicited.
Overall, the results showed that study participants generally shared the same or similar emotional responses to each of the videos, providing a wealth of data that allowed researchers to identify 27 distinct categories of emotion.
Through statistical modeling and visualization techniques, the researchers organized the emotional responses to each video into a semantic atlas of human emotions. On the map, each of the 27 distinct categories of emotion corresponds to a particular color.
“We wanted to shed light on the full palette of emotions that color our inner world,” Cowen said.
Source: Yasmin Anwar – UC Berkeley
Image Source: NeuroscienceNews.com image is credited to Alan Cowen.
Original Research: Abstract for “Self-report captures 27 distinct categories of emotion bridged by continuous gradients” by Alan S. Cowen and Dacher Keltner in PNAS. Published online September 5 2017 doi:10.1073/pnas.1702247114
[cbtabs][cbtab title=”MLA”]UC Berkeley “Researchers Pinpoint 27 States of Emotion.” NeuroscienceNews. NeuroscienceNews, 7 September 2017.
<https://neurosciencenews.com/emotion-27-states-7431/>.[/cbtab][cbtab title=”APA”]UC Berkeley (2017, September 7). Researchers Pinpoint 27 States of Emotion. NeuroscienceNew. Retrieved September 7, 2017 from https://neurosciencenews.com/emotion-27-states-7431/[/cbtab][cbtab title=”Chicago”]UC Berkeley “Researchers Pinpoint 27 States of Emotion.” https://neurosciencenews.com/emotion-27-states-7431/ (accessed September 7, 2017).[/cbtab][/cbtabs]
Abstract
Self-report captures 27 distinct categories of emotion bridged by continuous gradients
Emotions are centered in subjective experiences that people represent, in part, with hundreds, if not thousands, of semantic terms. Claims about the distribution of reported emotional states and the boundaries between emotion categories—that is, the geometric organization of the semantic space of emotion—have sparked intense debate. Here we introduce a conceptual framework to analyze reported emotional states elicited by 2,185 short videos, examining the richest array of reported emotional experiences studied to date and the extent to which reported experiences of emotion are structured by discrete and dimensional geometries. Across self-report methods, we find that the videos reliably elicit 27 distinct varieties of reported emotional experience. Further analyses revealed that categorical labels such as amusement better capture reports of subjective experience than commonly measured affective dimensions (e.g., valence and arousal). Although reported emotional experiences are represented within a semantic space best captured by categorical labels, the boundaries between categories of emotion are fuzzy rather than discrete. By analyzing the distribution of reported emotional states we uncover gradients of emotion—from anxiety to fear to horror to disgust, calmness to aesthetic appreciation to awe, and others—that correspond to smooth variation in affective dimensions such as valence and dominance. Reported emotional states occupy a complex, high-dimensional categorical space. In addition, our library of videos and an interactive map of the emotional states they elicit are made available to advance the science of emotion.
“Self-report captures 27 distinct categories of emotion bridged by continuous gradients” by Alan S. Cowen and Dacher Keltner in PNAS. Published online September 5 2017 doi:10.1073/pnas.1702247114
