Mapping the Passions: Toward a High-Dimensional Taxonomy of Emotional Experience and Expression
Mapping the Passions: Toward a High-Dimensional Taxonomy of Emotional Experience and Expression
复制标题
DOI：
10.1177/1529100619850176
复制
发表时间：
2019-07-01
影响因子：
25.4
通讯作者：
Keltner, Dacher
中科院分区：
文献类型：
--
作者：
Cowen, Alan;Sauter, Disa;Keltner, Dacher
一个全面的人类情感图谱应该包括哪些内容？50年来，科学家们一直试图用“六种基本情绪”（愤怒、厌恶、恐惧、快乐、悲伤和惊讶）来描绘与情绪相关的体验、表达、生理和认知。关于这六种情绪和原型面部结构之间关系的说法为关于表情诊断价值的长期争论提供了基础（关于这场争论的回顾和最新部分，请参见Barrett et al.，第1页）。基于最近的实证研究结果和方法，我们提供了一种替代的概念和方法，揭示了更丰富的情感分类。语言可以可靠地区分出几十种不同的情感，它们在不同的环境中被唤起，并在面部、身体和声音的不同表情中被感知。传统的模型--包括基本的六个模型和情感环模型（效价和唤醒）--捕捉到了情感反应中系统性变异的一小部分。相反，与情绪相关的反应（例如，尴尬的微笑，胜利的姿势，同情的声音，不同表情的混合）可以用更丰富的情感模型来解释。鉴于这些发展，我们讨论为什么测试的基本六模型的情绪不是测试的诊断价值的面部表情更普遍。确定面部表情可以告诉我们的全部内容，无论是边缘还是与其他行为和上下文线索相结合，都需要使用大规模统计建模和机器学习方法将面部，身体和声音信号的高维连续空间映射到丰富的多方面体验上。
What would a comprehensive atlas of human emotions include? For 50 years, scientists have sought to map emotion-related experience, expression, physiology, and recognition in terms of the "basic six"-anger, disgust, fear, happiness, sadness, and surprise. Claims about the relationships between these six emotions and prototypical facial configurations have provided the basis for a long-standing debate over the diagnostic value of expression (for review and latest installment in this debate, see Barrett et al., p. 1). Building on recent empirical findings and methodologies, we offer an alternative conceptual and methodological approach that reveals a richer taxonomy of emotion. Dozens of distinct varieties of emotion are reliably distinguished by language, evoked in distinct circumstances, and perceived in distinct expressions of the face, body, and voice. Traditional models-both the basic six and affective-circumplex model (valence and arousal)-capture a fraction of the systematic variability in emotional response. In contrast, emotion-related responses (e.g., the smile of embarrassment, triumphant postures, sympathetic vocalizations, blends of distinct expressions) can be explained by richer models of emotion. Given these developments, we discuss why tests of a basic-six model of emotion are not tests of the diagnostic value of facial expression more generally. Determining the full extent of what facial expressions can tell us, marginally and in conjunction with other behavioral and contextual cues, will require mapping the high-dimensional, continuous space of facial, bodily, and vocal signals onto richly multifaceted experiences using large-scale statistical modeling and machine-learning methods.