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Abstract
Emotions are viewed as having evolved through their adaptive value in dealing with fundamental life-tasks. Each emotion has unique features: signal, physiology, and antecedent events. Each emotion also has characteristics in common with other emotions: rapid onset, short duration, unbidden occurrence, automatic appraisal, and coherence among responses. These shared and unique characteristics are the product of our evolution, and distinguish emotions from other affective phenomena.
... Given the increasing popularity of online learning, investigating methods for detecting emotional states associated with learning has become increasingly important. There is a difference between basic emotions (Ekman, 1992) and academic emotions (Pekrun, 2000). While basic emotions are universal, they provide limited insight into learning, academic emotions are directly linked to students' achievement, cognitive processes, learning topics, and social interactions within the learning environment Therefore, more attention should be given to emotional states that are related to learning, the learning-centered affective states (LCAS) (Bosch et al., 2015). ...
... There are different theories regarding the different families of emotional models. Discrete models, the theorists in this suggest the existence of a set of core emotions that are universally shared among cultures such as the set from Ekman (Ekman, 1992) or Plutchik (Plutchik, 1980). Dimensional models, (Russell, 1980), Mehrabian (1980), this model suggests that all emotions are represented in a 3-dimensional space, with pleasure-arousaldominance as dimensions, a model usually used for studying emotions through nonverbal communication. ...
The significance of students’ affective states in educational settings is widely acknowledged. While face-to-face learning allows teachers to discern these states through non-verbal cues, online learning presents challenges due to the absence of such cues. This calls for research exploring methods to study students’ learning-centered affective states (LCASs) in online learning with the use of technology. The common limitation of relevant research is that it is limited to basic emotions and is not conducted in a controlled setting with standardized stimuli. In this paper, we present a set of design principles for educational content aiming at eliciting relevant LCASs: boredom, confusion, frustration, curiosity, and engagement, drawing insights from both literature and experts. Moreover, we provide a proof of concept through the exemplification of these principles: a set of educational videos evaluated by participants (N = 63) in an iterative study setup, serving as standardized stimuli.
... Despite steady progress in speech emotion recognition (SER) through deep architectures and selfsupervised representations, evaluation remains constrained by datasets predominantly built around a limited set of "basic" emotions [8,38]. Established benchmarks such as IEMOCAP [3], RAVDESS [19], and CREMA-D [4] have been invaluable for the field but exhibit three fundamental limitations: ...
... While these corpora provide clean labels and high acoustic quality, they share four persistent weaknesses. First, they use restrictive taxonomies-typically Ekman's six basic emotions [8]-omitting compound or socially nuanced states such as embarrassment, envy, or contemplation [27,5]. Second, their acted prosody exaggerates emotional cues and reduces generalization to spontaneous speech [20]. ...
The advancement of text-to-speech and audio generation models necessitates robust benchmarks for evaluating the emotional understanding capabilities of AI systems. Current speech emotion recognition (SER) datasets often exhibit limitations in emotional granularity, privacy concerns, or reliance on acted portrayals. This paper introduces EmoNet-Voice, a new resource for speech emotion detection, which includes EmoNet-Voice Big, a large-scale pre-training dataset (featuring over 4,500 hours of speech across 11 voices, 40 emotions, and 4 languages), and EmoNet-Voice Bench, a novel benchmark dataset with human expert annotations. EmoNet-Voice is designed to evaluate SER models on a fine-grained spectrum of 40 emotion categories with different levels of intensities. Leveraging state-of-the-art voice generation, we curated synthetic audio snippets simulating actors portraying scenes designed to evoke specific emotions. Crucially, we conducted rigorous validation by psychology experts who assigned perceived intensity labels. This synthetic, privacy-preserving approach allows for the inclusion of sensitive emotional states often absent in existing datasets. Lastly, we introduce Empathic Insight Voice models that set a new standard in speech emotion recognition with high agreement with human experts. Our evaluations across the current model landscape exhibit valuable findings, such as high-arousal emotions like anger being much easier to detect than low-arousal states like concentration.
... Emotion analysis differs from sentiment analysis as it is a fine-grained classification of text based on emotional categories. Six basic emotions (anger, fear, sadness, enjoyment, disgust, and surprise) are defined by (Ekman 1992), and most emotion analysis studies focus on these emotions. In (Ekman 1992), the author further argues that these emotions can differ in antecedent events, behavioral response, physiology, etc. ...
... Six basic emotions (anger, fear, sadness, enjoyment, disgust, and surprise) are defined by (Ekman 1992), and most emotion analysis studies focus on these emotions. In (Ekman 1992), the author further argues that these emotions can differ in antecedent events, behavioral response, physiology, etc. To classify emotions, following (Zhunis et al. 2022), we used the Semeval-2018 Twitter dataset (Mohammad et al. 2018) with 11 emotions (anger, anticipation, dis- gust, fear, joy, love, optimism, pessimism, sadness, surprise, and trust) to fine-tune a pre-trained language model using joint representation from our sentiment model. ...
The Black Lives Matter (BLM) movement seeks to spread awareness and fight against social and racial injustice. In 2020, BLM-related discussions surged on social media after the death of George Floyd and the protests that followed. Previous works have qualitatively analyzed the scaling, dynamics, and topics of BLM discussions on social media. However, very few works have studied the offensive content, the emotions expressed, and the topics of offensive discussions in BLM-related discussions. In this measurement study, to examine offensive language and emotion, we conduct a largescale study of BLM discussions on Twitter. We first develop a classifier that uses sentiment representation to aid offensive language detection. We then develop an emotion classifier based on deep attention fusion with sentiment features to classify emotions. We further use topic modeling to analyze the topics of offensive tweets. Our analysis of over 20 million tweets revealed that offensive tweets peeked in the weeks following George Floyd’s death and rapidly decreased but remained stable. The analysis further revealed that negative emotions were the most expressed emotions. Offensive reply network analysis reveals that most offensive replies are unidirectional. Our contribution in this work is five-fold: (1) We identify offensive content during BLM protests; (2) we identify online emotions that were significant in the offensive and non-offensive content during the protests; (3) we assess the characteristics of users who replied offensively and those who are the recipients of offensive content; (4) we assess emotion dynamics across offenders and recipients; (5) we identify the hot topics that most drove the offensive content on Twitter. Our work offers important implications for content moderation and the conscious and unconscious attitudes towards the black/African American community.
... Por outro lado, há abordagens que consideram as emoções como respostas rápidas e transitórias a determinadas situações e contextos. (EKMAN, 1992) Nesse universo complexo das emoções, grande parte dos estudos tem como base as chamadas emoções discretas, que seriam emoções -positivas ...
... (BRADER;MILLER, 2011;PECK, 2001;SEO, 2013) As emoções discretas estariam relacionadas às chamadas emoções básicas, que seriam um conjunto de componentes neurológicos, corporais e motivacionais gerados de maneira rápida, automática e inconsciente. (EKMAN, 1992;IZARD, 2007b) Nesta seção, exploramos brevemente algumas das principais abordagens teóricas das emoções utilizadas por pesquisadores da área de comunicação e política e que partem das categorias de emoções apresentadas acima. Também não há consenso sobre essa sistematização de abordagens teóricas. ...
A obra visa abordar técnicas e instrumentos de pesquisa de modo mais apropriado e coerente com as indignações e os problemas nessa área interdisciplinar de conhecimento. Os métodos são tratados de maneira didática e sistemática, a fim de permitir um entendimento aprofundado e contextualizado sobre várias estratégias analíticas, dimensões e ângulos para tratar complexos processos comunicativos que atravessam a política institucional formal, organizações do mercado, associações cívicas e as experiências das pessoas em diferentes domínios sociais.
... Social cognition training in psychotic conditions SC emerged at the intersection of cognitive, developmental and social psychology, and neuroscience, integrating diverse perspectives. It draws from social learning theory 22 , which emphasizes observational learning and modelling; attribution theory 23,24 , which explores how individuals infer causes for others' behaviours; Theory of Mind frameworks 25-27 , which focus on mindreading and perspective-taking; and neuroscientific insights into social brain networks 28,29 . Attachment theory 30,31 highlights how early caregiver relationships shape mentalizing and emotion regulationcore aspects of SC. ...
... Social cognition training in psychotic conditions SC emerged at the intersection of cognitive, developmental and social psychology, and neuroscience, integrating diverse perspectives. It draws from social learning theory 22 , which emphasizes observational learning and modelling; attribution theory 23,24 , which explores how individuals infer causes for others' behaviours; Theory of Mind frameworks [25][26][27] , which focus on mindreading and perspective-taking; and neuroscientific insights into social brain networks 28,29 . Attachment theory 30,31 highlights how early caregiver relationships shape mentalizing and emotion regulationcore aspects of SC. ...
... De esta forma, se consigue determinar si en el conjunto de palabras se expresa un sentimiento positivo, negativo o neutro. De ahí que 1 A pesar de que los términos emoción y sentimiento no son totalmente equivalentes, en este trabajo su uso se hará indistintamente dado que así se ha estandarizado en la mayoría de los trabajos consultados (Damasio 1994(Damasio , 2003(Damasio , 2005Ekman 1992). en este trabajo se aborde el estudio de los valores sociales y su vinculación con las emociones, así como la polaridad y la intensidad de las emociones detectadas en el discurso oral, a través del AS. ...
... En relación con una clasificación de las emociones, se han consultado diversas fuentes (Bisquerra y Laymuns 2022;Ekman 1992;Goleman 1995). Los primeros (2022) distinguen dos grandes categorías: las emociones negativas, que son aquellas que producen malestar y las positivas, que generan bienestar. ...
Sentiment analysis is a topic that has been researched in several fields, however, few studies have been carried out in the oral language of architecture. This article analyzes a corpus of two architecture podcasts in Spanish, with the aim of identifying the relationship between emotion and values in this genre. It is based on the hypothesis that emotion is linked to certain social values. The qualitative and quantitative methodology is based on Critical Discourse Analysis and Corpus Linguistics. After the qualitative analysis, the sentiment analysis tool Lingmotif (Moreno-Ortiz 2021) has been applied. It has provided quantitative data on the presence of emotion, its polarity, its intensity indices, as well as clouds of emotionally charged words linked to social values. This work contributes to the development of sentiment analysis in the field of podcasts and provides reasonable information on the relationship between values and emotion.
... Multi-modal Emotion Detection through Visuals Emotion detection through visual modalities involves extracting facial features from video frames and analyzing them to classify emotions. This approach typically focuses on Ekman's six basic emotions: happiness, sadness, fear, anger, surprise, and disgust [10]. This methodology synthesizes innovations from deep learning architectures, temporal-spectral processing, and mobile optimization to achieve state-of-the-art emotion recognition accuracy (88.8% F1-score) with 190ms latency on mobile devices. ...
Undergraduate students face increasing academic and personal pressures, often leading to stress and emotional distress. Traditional single-modal emotion recognition systems, relying solely on facial or vocal analysis, struggle with accuracy due to environmental variations and limited contextual awareness. This research proposes a multi-modal AI-driven emotion recognition system that integrates facial and vocal data for enhanced real-time emotional detection and response. The system leverages Vision Transformers (ViTs) for facial feature extraction and Mel-Frequency Cepstral Coefficients (MFCC) for speech-based emotion analysis, ensuring improved classification through confidence-weighted temporal fusion. Additionally, an adaptive response generation module utilizes natural language processing (NLP) and text-to-speech (TTS) synthesis for human-like interactions. To enable scalable mobile deployment, the model is optimized with quantized lightweight transformers, achieving sub 300ms inference latency. Bias mitigation techniques ensure fairness across demographic groups. This research contributes to affective computing, human-computer interaction, and AI-driven emotional intelligence, offering a scalable and ethically responsible solution for virtual counseling, AI-assisted tutoring, and mental health support.
... Com isso, se obtém insights sobre tipos de conteúdo mais eficazes em gerar interação e como as emoções expressas nas postagens impactam o engajamento (Berger;Milkman, 2012). Para as publicações, foram analisados os termos mais relacionados a sinônimos de determinada emoção do modelo de Ekman, que categorizam aquelas expressas nos posts (Ekman, 1992). ...
... The dimensional model, which organizes emotions along continuous dimensions such as valence and arousal, has provided valuable insights into the general affective states that influence cognitive processes (Russell, 1980). By contrast, the discrete model of emotions, which classifies emotions into discrete categories, such as happiness, sadness, anger, fear, and disgust, could offer a more nuanced understanding of how specific emotions interact with cognitive functions like working memory (Ekman, 1992). For example, while positive emotions (e.g., happiness) may enhance cognitive flexibility and task performance, negative emotions (e.g., anger or fear) may impede cognitive processes due to their tendency to narrow attention (Isen, 2001). ...
The aim of this study was to investigate the impact of working memory overload on emotional processing and recognition memory. Firstly, to study emotional processing, subjective and fNIRS correlates were measured while inducing emotions using affective pictures presented for 6 s. A recognition memory task was then administered, in which participants were required to indicate whether each affective stimulus was new or had previously been used in the passive viewing task. A sample of 70 healthy volunteers (44 women) were divided into an experimental group in which working memory was overloaded during the emotion induction procedure, and a control group in which working memory was not overloaded. Regarding the effect of working memory overload on emotional processing, the results showed that the experimental group rated negative stimuli as less unpleasant. Additionally, this group presented higher fNIRS activations in the dorsolateral prefrontal cortex (DLPFC), particularly to high arousal stimuli. Meanwhile, the findings revealed better recognition for negative and high arousal stimuli in the experimental group. Overall, our findings provide further evidence on the modulation of emotional processing and recognition memory as a function of working memory overload, while highlighting the importance of the DLPFC in emotion processing and cognitive load management.
... This process is integral to multiple domains, including smart governance, business, and organizations, where it is applied to various data formats such as audio, text, and video. The theoretical foundation for EC is often grounded in psychological theories of emotion, such as Plutchik's "Wheel of Emotions" [7] and Ekman's theory of basic emotions [8]. Automated EC, which includes Single-Label Emotion Classification (SLEC) and Multi-Label Emotion Classification (MLEC), has become essential due to the vast amount of text available online. ...
Multi-label emotion classification (MLEC) for low-resource languages like Arabic faces significant challenges due to class imbalance and label correlations, particularly in accurately predicting minority emotions. This study propose a novel framework combining stacked contextual embeddings, meta-learning, and a hybrid loss function to address these issues. First, we generate enriched embeddings by fine-tuning and stacking three Arabic language models (ArabicBERT, MarBERT, AraBERT). These embeddings are processed by a Bi-LSTM meta-learner for sequence learning, followed by a fully connected network for classification. To mitigate class imbalance and leverage label dependencies, we introduce a hybrid loss integrating contrastive learning (CL), label correlation matrices (LCM), and class weighting (CW). Extensive experiments on the SemEval-2018 Task 1-Ec-Ar dataset demonstrate state-of-the-art performance, with a Jaccard accuracy of 0.81, F1-score of 0.67, and Hamming loss of 0.15. Ablation studies confirm the contributions of each component, while class-wise analysis shows our hybrid loss reduces disparities between majority and minority classes by up to 22%. Beyond Arabic MLEC, this work offers a generalizable framework adaptable to other languages and domains, advancing emotion analysis in low-resource settings.
... Hasil survey lokasi dan juga data wawancara menunjukkan bahwa keterbatasan lahan di Kecamatan Sumedang Selatan adalah hasil dari interaksi kompleks antara pertumbuhan penduduk dan pembangunan infrastruktur, dampak yang ditimbulkan mencakup penurunan produktivitas pertanian termasuk di dalamnya perikanan, kesulitan akses lahan bagi masyarakat berpenghasilan rendah, hingga degradasi lingkungan. Berikut adalah karakteristik wilayah terpilih yang cocok dengan berikut beberapa syarat yang perlu dipenuhi oleh kelompok perikanan untuk menerapkan budidaya Yumina ( Antusiasme masyarakat dapat dipahami melalui beberapa teori: 1) Teori Emosi: Antusiasme adalah emosi positif yang dapat memengaruhi motivasi dan perilaku masyarakat (Ekman, P. 1992). 2) Teori Motivasi: Antusiasme dapat memicu masyarakat untuk terlibat dalam aktivitas atau mendukung suatu gagasan (Maslow, A. H. 1943). ...
Yumina-Bumina ialah metode budidaya perikanan yang mengintegrasikan antara ikan dengan sayuran dan buah-buahan. Dalam budidaya Yumina-Bumina terdapat empat sistem yang dikenal, yaitu: sistem rakit, aliran atas, aliran bawah, dan pasang surut. Yumina-Bumina adalah salah satu inovasi dari teknologi akuaponik yang berlandaskan efisiensi air dan efisiensi lahan dengan menggabungkan budidaya ikan (akuakultur) dan pertumbuhan tanaman tanpa tanah (hidroponik). Journal ini menyajikan pembahasan mengenai serangkaian kegiatan sosialisasi sebagai bentuk pengabdian kepada masyarakat. Kegiatan sosialisasi ini mencakup observasi lapangan, wawancara dan kegiatan sosialisasi itu sendiri. Rangkaian kegiatan sosialisasi sistem rakit YUMINA BUMINA ini bertujuan untuk mengidentifikasi karakteristik apa saja yang dimiliki oleh wilayah binaan, yaitu Kecamatan Sumedang Selatan, yang sesuai untuk penerapan budidaya Yumina Bumina menggunakan sistem rakit. Selain itu, kegiatan ini juga bertujuan untuk memberikan pemahaman tentang cara kerja sistem rakit YUMINA BUMINA dan memberdayakan potensi masyarakat dengan sumber air dan lahan yang terbatas secara maksimal. Kegiatan ini merupakan kegiatan partisipatif yang diharapkan dapat mendorong masyarakat untuk dapat menerapkan budidaya YUMINA BUMINA menggunakan sistem rakit.
... Feldman Barrett (2020) De modo complementar à valência e à excitação, o conceito de qualia (Nagel, 1974;Jackson, 1982;Chalmers, 1996;Kriegel, 2023) (Ekman, 1992;Izard, 2011;Tompkins, Panksepp, 2011;Plutchik, 1980). Damasio (1999;2010) estabelece duas categorias para as emoções: primárias e secundárias. ...
O objetivo deste artigo é apresentar o estado da arte da noção de afeto, explicitando suas delimitações conceituais e destrinchando as complicações terminológicas que envolvem a relação dessa ideia a categorias lindeiras como emoção e sentimento. Para tanto, por meio de uma ampla pesquisa bibliográfica, promovemos um sobrevoo sintético pela história de maturação e desenvolvimento da noção de afeto, desde algumas de suas elaborações mais importantes nos campos da filosofia, sociologia, psicologia e das neurociências até a sua apropriação no terreno dos estudos da Linguagem. Em seguida, discutimos as diferentes acepções e compreensões atribuídas aos afetos na literatura contemporânea que dialoga mais intimamente com o campo dos estudos sobre o impacto das experiências afetivas no ensino-aprendizagem de línguas, privilegiando uma concepção corporificada de afeto. Finalmente, delimitamos as fronteiras e espaços porosos entre as categorias de afeto, emoção e sentimento, destacando os desdobramentos da adoção de uma perspectiva que reconcilie corpo e mente no estudo do papel da afetividade no processo de ensino-aprendizagem de línguas e apresentando perspectivas futuras para pesquisas sobre o afeto.
... These studies support its practical usability in both experimental and in-the-wild settings. Moreover, MorphCast's emotion classification architecture has been shown to align with established frameworks such as Ekman's discrete model [25], providing methodological consistency with prior validated facial emotion recognition (FER) systems. ...
Color blindness can create challenges in recognizing visual cues, potentially affecting players’ performance, emotional involvement, and overall gaming experience. This study examines the impact of color blindness on player engagement and emotional experiences in digital games. The research aims to analyze how color-blind individuals engage with and emotionally respond to games, offering insights into more inclusive and accessible game design. An experiment-based study was conducted using a between-group design with a total of 13 participants, including 5 color-blind and 8 non-color-blind participants (aged 18–30). The sample was carefully selected to ensure participants had similar levels of digital gaming experience and familiarity with digital games, reducing potential biases related to skill or prior exposure. A custom-designed game, “Color Quest,” was developed to assess engagement and emotional responses. Emotional responses were measured through Emotion AI analysis, video recordings, and self-reported feedback forms. Participants were also asked to rate their engagement and emotional experience on a 1 to 5 scale, with additional qualitative feedback collected for deeper insights. The results indicate that color-blind players generally reported lower engagement levels compared to non-color-blind players. Although quantitative data did not reveal a direct correlation between color blindness and visual experience, self-reported feedback suggests that color-related design choices negatively impact emotional involvement and player immersion. Furthermore, in the survey responses from participants, color-blind individuals rated their experiences lower compared to individuals with normal vision. Participants emphasized that certain visual elements created difficulties in gameplay, and alternative sensory cues, such as audio feedback, helped mitigate these challenges. This study presents an experimental evaluation of color blindness in gaming, emphasizing how sensory adaptation strategies can support player engagement and emotional experience. This study contributes to game accessibility research by highlighting the importance of perceptual diversity and inclusive sensory design in enhancing player engagement for color-blind individuals.
... In the study, 547 participants rated these emotion labels along dimensions of valence, arousal, focus, and dominance. The affect labels of interest were anger, surprise, happiness, fear, disgust, satisfaction, sadness, sleepiness, and relaxation for basic emotions (Ekman, 1992). Items satisfaction, sleepiness, and relaxation were obtained from probabilistic mapping of emotion labels (Heffner & FeldmanHall, 2022) since six basic emotions did not occupy full emotion space defined by valence and arousal. ...
Measuring emotion remains a persistent challenge due to poor alignment between theoretical constructs and available measurement tools, as well as issues of underspecificity and low reliability. Dimensional approaches—especially those incorporating social-affective dimensions—are being explored for their potential to enhance the quality of emotional data. Recent advances in large language models (LLMs) offer a novel opportunity to improve both emotion measurement and communication, leveraging their exceptional pattern recognition capabilities and capacity for multi-modal generation. In this study, we investigate for the first time whether LLMs can successfully mediate human emotional communication through analogical representations—expressing feelings not by naming them, but by evoking them.
We utilized multi-dimensional affective ratings from 547 participants across eighteen emotion labels obtained in a prior study. Based on this human emotion representation and custom-designed prompts, an LLM generated both textual and high-resolution (1024 × 1024) image outputs for each label. Two independent raters selected ten texts and one image per label, which were then presented to a new sample of 138 participants via an online psychology experiment platform. Participants rated these multi-modal stimuli using the same multi-dimensional affective scale. Angular and Euclidean distance metrics were used to evaluate the similarity between participants’ affective responses and the original ratings.
Emotional experiences for fifteen out of eighteen emotion labels were successfully reconstructed through exposure to LLM-generated stimuli. However, three emotions—disgust, satisfaction, and gratitude—were not effectively conveyed through either modality. The results also highlighted contextual modulation of emotion expression, influenced by media format and individual mood pathology. Across all categories, image-based stimuli evoked stronger affective responses than text. Moreover, participants with elevated depressive symptoms exhibited heightened emotional reactivity to shared stimuli—a potential affective signature of depression, rather than a general emotional amplification.
This study introduces a novel pipeline for eliciting and transmitting human emotional experiences through language models using analogy as a bridge—a method that is both replicable and empirically validated. Still, establishing true equivalence of emotional experiences requires further theoretical and mathematical development. Future directions include incorporating physiological markers, comparing across LLM architectures, and refining generalizability for broader human-centered applications in affective computing.
... Moreover, exploratory analyses did not provide evidence that self-reported measures and nasal cutaneous temperature changes were correlated. This relates to the notion of response coherence (e.g., Ekman 1992;Lazarus 1991;Levenson 1994), showing that different emotional response systems (experiential, behavioral, physiological) do not always align perfectly (Brown et al. 2020;Mauss et al. 2005). Alternatively, the observed discrepancy between self-reported and thermal responses suggests that the current hypothetical Cyberball games, using mental imagery rather than deception or real interactions, do not sufficiently provoke ANS activity detectable through facial temperature changes. ...
Ostracism (feeling ignored and excluded) triggers psychophysiological responses associated with distress. We investigated different coping responses after ostracism and explored whether these were preceded by unique facial thermal signatures, reflecting autonomic nervous system (ANS) activity. Using thermal infrared imaging, we recorded facial cutaneous temperature variations in female participants (N = 95) experiencing inclusion and ostracism using hypothetical Cyberball games. Coping after ostracism was assessed during a hypothetical Allocation Game, where participants could do nothing (withdrawal), reduce (antisocial), or increase (prosocial) the hypothetical earnings of their ostracizer. Contrary to expectations, most participants chose to withdraw (52%), with fewer opting for antisocial responses (30%) or prosocial responses (18%) after ostracism. Results from linear mixed‐effects modeling revealed that substantial temperature variability occurred only in the nose region of the face. Both ostracism and inclusion showed a decrease in nasal temperature relative to baseline, but the average drop was greater during inclusion, suggesting stronger ANS activation during inclusion rather than ostracism. Crucially, exploratory findings showed that only participants who responded antisocially after ostracism exhibited steeper decreases in nasal temperature during ostracism compared to inclusion. This pattern suggests greater physiological reactivity among antisocial responders, particularly in contrast to those who chose to withdraw. Future research should integrate thermal imaging with other physiological measures and strengthen ostracism manipulations to understand the relationship between thermal responses and different coping behaviors.
... Temelde, bireyin yaşamını sürdürmesine, uyum sağlamasına ve sosyal ilişkilerini düzenlemesine yardımcı olan evrimsel bir işlev taşırlar (Izard, 2010). Psikoloji literatüründe duygular genellikle kısa süreli, yoğun ve belirli bir nesneye ya da duruma yönelik olarak ortaya çıkan zihinsel durumlar olarak tanımlanır (Ekman, 1992). Bu yönüyle duygular, ruh hali ya da motivasyon gibi daha geniş zaman dilimine yayılan duygusal süreçlerden ayrılmaktadır. ...
Emotions are complex internal experiences that integrate cognitive, physiological, and behavioral elements, forming the basis of an individual's interaction with their environment. Effectively recognizing, expressing, and managing emotions is essential for both psychological well-being and social functionality. Emotion regulation, in this context, emerges as a critical psychological skill that enables individuals to maintain internal equilibrium and engage in healthy interpersonal relationships. According to Gross’s process model, emotion regulation involves strategies applied before or after emotions arise, aiming to modify emotional experiences and responses. This study examines the developmental foundations of emotion regulation, emphasizing the role of familial influence and parenting styles during early childhood. It also investigates how individuals manage their emotions in everyday life depending on social contexts and their interactions with others. Within the framework of interpersonal emotion regulation principles, the regulatory function of the social environment is analyzed. The findings indicate that emotion regulation is not merely an internal mechanism but a socially embedded process shaped by ongoing interactions. Supporting these skills contributes significantly to individual well-being and the strengthening of interpersonal bonds, underscoring its importance in psychological and social development. Keywords: Emotion, emotion regulation, Gross’s process model, interpersonal relationships, family influence, social context
... The set of emotions consists of the seven emotions listed above according to Ekman (1992). The default emotion status is set to "neutral". ...
... Emotion analysis is derived from the sentiment analysis domain, where human orientation can be judged from a given piece of text data [2]. Paul Ekman initially suggested six emotional states: "joy", "sadness", "disgust", "anger", "enjoyment", and "surprise" [3]. Robert Plutchik in [4] then extended Paul's list by adding two more emotion states: "trust" and "anticipation". ...
Emotion expression modes play a significant role in human communication. Humans use emotions to convey their state of mind to each other on platforms such as X (formerly Twitter), Facebook, and other online social networks. People often express their emotions using free text, which triggers a vast research area of emotion detection and analysis. This work aims to detect and analyze emotions from unstructured text data. For this purpose, this research study proposes a solution to the problem by building a deep artificial neural network model using trainable and pre-trained word embedding methods. Afterward, the performance of the models developed with different word embeddings is evaluated using the performance metrics. Experimental works demonstrate that the deep artificial neural network with trainable word embedding surpassed all other models by achieving 67.36% accuracy, 53.27% recall, 82.62% precision, and 64.50% F-measure.
... For explicit tasks (EERC, EEFC), we used Daily-Dialog (Li et al., 2017), which consists of daily life dyadic textual conversations. The utterances are annotated with seven emotion labels: Ekman's six primary emotions (anger, disgust, fear, happiness, sadness, surprise) (Ekman, 1992) and no emotion. ...
... Theories of emotion are divided into neurological, physiological, and cognitive categories [17], including the Evolutionary Theory of Emotion [18], James-Lange theory [19], and Schachter-Singer Theory [20]. Emotions can be gauged through dimensional approaches, like Russell's circumplex model [21], or categorical approaches, such as the six basic emotions [22]. In contrast, sentiment refers to the enduring positive or negative feelings shaping opinions [23], involving a mix of emotions, cognition, and behavior [24]. ...
... Categorical models define a fixed set of discrete emotional states. Examples include Shaver's [42] (sadness, love, joy, anger, surprise, and fear), Ekman [14] (joy, anger, fear, disgust, sadness, and surprise), and Plutchik [38] (anticipation, surprise, anger, fear, trust, disgust, joy, and sadness). In MMAFFBen, there are two kinds of emotion classifications, including single-class classification (i.e. ...
Large language models and vision-language models (which we jointly call LMs) have transformed NLP and CV, demonstrating remarkable potential across various fields. However, their capabilities in affective analysis (i.e. sentiment analysis and emotion detection) remain underexplored. This gap is largely due to the absence of comprehensive evaluation benchmarks, and the inherent complexity of affective analysis tasks. In this paper, we introduce MMAFFBen, the first extensive open-source benchmark for multilingual multimodal affective analysis. MMAFFBen encompasses text, image, and video modalities across 35 languages, covering four key affective analysis tasks: sentiment polarity, sentiment intensity, emotion classification, and emotion intensity. Moreover, we construct the MMAFFIn dataset for fine-tuning LMs on affective analysis tasks, and further develop MMAFFLM-3b and MMAFFLM-7b based on it. We evaluate various representative LMs, including GPT-4o-mini, providing a systematic comparison of their affective understanding capabilities. This project is available at https://github.com/lzw108/MMAFFBen.
... Player emotions are analyzed to understand their impact on reviews. Emotions are grouped into six according to [19], namely positive emotions (joy, surprise) and negative emotions (anger, disgust, fear, and sadness), as well as one additional category, namely neutral. This model has been used effectively in various previous text analysis studies [20] [21]. ...
The video game industry is experiencing rapid growth, with the fighting game genre remaining a favorite due to its tactical challenges and deep mechanics. This study explored the relationship between playtime, game design, and game mechanics to positive reviews from players, using Large Language Models (LLMs) for sentiment and emotion analysis. The data was collected from more than 200,000 Steam user reviews on 12 popular fighting games. The results show that the correlation between playtime and positive reviews tends to be weak, although in some titles, longer playing duration is associated with better sentiment. In terms of game design, players prefer games with fantasy settings (92.34%), 2D graphics (94.21%), and anime visual style (95.12%), which significantly drives positive reviews. In the mechanical aspects of the game, features such as multiple meters (93.11%), advanced blocking (93.56%), and wall boundaries (91.72%) get higher satisfaction, suggesting that the complexity and variety of mechanics can increase player engagement. LLM-based sentiment analysis also reveals that technical factors play an important role in player perception. The most common complaints in negative reviews relate to lag, character balancing, and additional content quality (DLC).
... Human emotional expression involves complex interplay between facial expressions, body language, vocal intonation, and contextual appropriateness (Ekman, 1992). AGI systems in metaverse environments must not only recognize and interpret human emotions but also generate appropriate emotional responses through their virtual avatars. ...
As artificial general intelligence (AGI) systems advance toward human-level cognitive capabilities, their integration into metaverse platforms presents unprecedented opportunities for creating anthropomorphic digital entities. This article examines the theoretical foundations, technical challenges, and sociocultural implications of AGI systems designed to emulate human behavior, emotions, and social interactions within virtual environments. Through analysis of current developments in embodied AI, virtual presence, and human-computer interaction, we explore how AGI might achieve convincing human-like representation in digital spaces, the motivations driving such developments, and the potential consequences for human identity and social structures in virtual worlds.
... Os modelos discretos consideram a existência de várias emoções básicas que podem ser reconhecidas de forma universal. Ekman (1992) considera as emoções como discretas e mensuráveis com características únicas, sendo que todos reconhecem e expressam da mesma forma independente de questões culturais, resumindo-as a seis emoções básicas como felicidade, raiva, tristeza, medo, surpresa e nojo. ...
O comportamento humano é impactado por diferentes fenômenos que afetam a percepção e interação. Em cada cultura são usadas diferentes palavras para descrever como alguém se sente. Os fenômenos afetivos podem provocar diferentes reações fisiológicas, cognitivas ou comportamentais podendo afetar ações e reações de uma pessoa. No ambiente educacional os fenômenos afetivos são essenciais na aprendizagem, podendo impactar a motivação e a atenção. Dessa forma, entender as relações do estado afetivo e o contexto educacional pode auxiliar na identificação de fatores que impactam de forma negativa ou positiva o aluno. Este artigo propõe a ontologia OntoUaffect para representar informações de estados afetivos, o contexto educacional e pessoal do aluno. A ontologia foi desenvolvida utilizando o software Protégé e a linguagem Python. Para avaliação da ontologia foram utilizados dados reais coletados com alunos do ensino médio. A partir de consultas SPARQL foi possível obter resultados que respondem as questões propostas de identificação do estado afetivo do aluno em eventos específicos, assim como a relação das variáveis de contexto educacional, demonstrando a contribuição da ontologia proposta.
... The lack of correlation between manual and automated coding in the context of this study suggests that manual coding was more sensitive in detecting subtle differences in fairly neutral televised faces as Fac-eReader detected even less activity in darts players faces compared to FACS coders. Although, the FACS was developed alongside the theoretical perspective of Basic Emotion Theory (Ekman, 1992;Keltner et al., 2019), which argues for universal basic emotions that are associated with distinct facial expressions, the present pattern of results does not suggest that a distinct facial expression exists in professional darts players that is predictive of good or poor darts performance. Hence, when observers of darts competitions were shown to be able to accurately infer performance tendencies based on thin-slices of pre-performance nonverbal behavior , this was likely not informed by distinct facial expressions coinciding with good or poor performance. ...
The main objective of the present research was to use FACS on the televised pre-performance facial behavior of professional darts players to investigate if the facial behavior differed between successful and unsuccessful performances. A secondary goal of this study was to test if manual facial coding differed from automated coding using Noldus FaceReader. Therefore, a random sampling methodology was utilized to assemble video clips of the facial behavior of all players immediately before throwing darts in the 2017 World darts Championship in two performance categories, poor and good performance (10 clips per players respectively). Two FACS-certified coders blind to performance condition coded the activation intensity of
27 distinct muscle groups in the face (i.e., action units) and were compared to Noldus FaceReader output. Results showed very limited facial muscle movements in the videos across both performance categories and hardly any correlation between FACS and FaceReader data. However, multivariate data analysis of the FACS data revealed less intense action unit activity before good performance vs. poor performance. More specifically, successful darts performance was associated with lower muscle activity around the eyes and the mouth. These findings are discussed in light of previous literature suggesting that the face can be indicative of levels of arousal and anxiety and that low levels of arousal and anxiety prior to fine sensorimotor coordination are associated with performance in these situations.
Aquest article examina la relació temporal entre la simpatia partidista i la intenció de vot en tres partits clau del sistema polític espanyol: PSOE, PP i VOX. S'estudia la simpatia cap als partits, com a avantsala a la decisió de vot. A partir de sèries temporals mensuals entre abril de 2020 i juliol de 2023, s'aplica una anàlisi de correlació creuada per avaluar si la simpatia funciona com un indicador avançat del vot. S'empra dades amb periodicitat mensual del Centre d'Investigacions Sociològiques (CIS), amb un total de 72 observacions consecutives, la qual cosa permet estimar 100.000 euros de fins a sis mesos amb potència estadística suficient (Cohen, 2013). Es van aplicar proves de causalitat de Granger i es van estimar models VAR amb funcions d'impuls-resposta (IRF) per als tres partits analitzats. Els resultats mostren patrons diferenciats; en el PP, la simpatia s'associa de forma anticipada al vot; al PSOE, la relació és més sincrònica i contingent; a VOX, més feble i volàtil. A més, s'identifica una relació creuada asimètrica entre simpatia cap a VOX i vot al PP. Es conclou que la simpatia partidista és una variable significativa en la dinàmica del vot, amb implicacions teòriques i metodològiques per a l'estudi del comportament electoral.
Este artigo examina a relación temporal entre a simpatía partidista e a intención de voto en tres partidos clave do sistema político español: PSOE, PP e VOX. Estímase a simpatía cara aos partidos, como antesala á decisión de voto. A partir de series temporais mensuais entre abril de 2020 e xullo de 2023, aplícase unha análise de correlación cruzada para avaliar se a simpatía funciona como un indicador adiantado do voto. Emprégase datos con periodicidade mensual do Centro de Investigacións Sociolóxicas (CIS), cun total de 72 observacións consecutivas, o que permite estimar rezagos de ata seis meses con potencia estatística suficiente (Cohen, 2013). Aplícanse probas de causalidade de Granger e estimáronse modelos VAR con funcións de impulso-resposta (IRF) para os tres partidos analizados. Os resultados mostran patróns diferenciados; no PP, a simpatía asociase de forma anticipada ao voto; no PSOE, a relación é máis sincrónica e continxente; en VOX, máis débil e volátil. Ademais, identifícase unha relación cruzada asimétrica entre simpatía cara a VOX e voto ao PP. Conclúese que a simpatía partidista é unha variable significativa na dinámica do voto, con implicacións teóricas e metodolóxicas para o estudo do comportamento electoral.
Positive emotions such as joy, delight and gratitude are beneficial in bringing about a sense of well-being and building positive attitudes among people. A lot research has pointed out that cultivating positive emotions support mental well-being, personal fulfilment and social good. The emerging field of Positive psychology as well as neuroscience has also laid stress on fostering positivity and recognising the role of positive emotions in building resilience, social connections, broadening mental perspectives, stimulating creativity, fostering problem-solving and overall life satisfaction. Resultantly, they also have a positive impact on immune function and overall physical health. However, it is essential to recognise the potential drawbacks of excessive positivity, such as overconfidence and the neglect of negative emotions, which can result in emotional exhaustion and burnout. Research highlights the benefits of positive emotions for psychological well-being, resilience, and social relationships, while also acknowledging the risks of blind optimism and selective attention. This chapter discusses the effects of too much positivity. Embracing a balanced view of positive emotions helps individuals effectively manage challenges and build meaningful relationships.
AI is revolutionizing our understanding of animal inner lives by decoding meanings in vocalizations, gestures & body language, illuminating emotions, relationships & cognition. Machine learning identifies subtle cues in whale song, primate calls & bird chirps, while computer vision tracks eye gaze & posture. Large datasets fuel AI pattern recognition for predictive models impossible manually. However, AI must be tailored to species-specific contexts, avoid anthropomorphic bias & collaborate with animal experts despite limited data. AI could vastly enrich our grasp of animal minds, facilitate inter-species communication & inspire compassionate conservation. The fusion of ethology, cognitive science & AI can enhance animal welfare & transform our comprehension of non-human cognition, helping us coexist with other sentient beings on Earth.
In this chapter, we explore the importance of studying emotional responses to exercise, focusing on the acute and chronic effects of exercise on the multifaceted and nuanced construct of emotion. We begin the chapter by identifying and discussing theoretical perspectives of emotion, ranging from discrete to dimensional conceptualizations, with the goal of operationalizing emotion and how it is studied in the context of psychophysiological research. Next, we provide an overview of how emotions are measured in exercise research, highlighting commonly used self-report instruments and psychophysiological methods. We then review the scientific evidence regarding emotional responses to both acute and chronic exercise and provide a summary and conclusions regarding the state of the evidence. Lastly, general suggestions for future research aiming to advance this line of inquiry are offered.
Se presentan resultados de un estudio exploratorio acerca de la relación entre emociones primarias y topografía de la hoja en que se pide ubicar imágenes que ilustran estas emociones. Se determina un doble eje de la hoja de trabajo: corporal y temporal.
Se halla una relación entre la percepción que los sujetos tienen de las emociones y el modo en que ubican en la hoja las imágenes de dichas emociones
Video emotion recognition (VER), situated at the convergence of affective computing and computer vision, aims to predict the primary emotion evoked in most viewers through video content, with extensive applications in video recommendation, human–computer interaction, and intelligent education. This paper commences with an analysis of the psychological models that constitute the foundation of VER theory. The paper further elaborates on datasets and evaluation metrics commonly utilized in VER. Then, the paper reviews VER algorithms according to their categories, and compares and analyzes the experimental results of classic methods on four datasets. Based on a comprehensive analysis and investigations, the paper identifies the prevailing challenges currently faced in the VER field, including gaps between emotional representations and labels, large-scale and high-quality VER datasets, and the efficient integration of multiple modalities. Furthermore, this study proposes potential research directions to address these challenges, e.g., advanced neural network architectures, efficient multimodal fusion strategies, high-quality emotional representation, and robust active learning strategies.
Emotional visual stimuli, whether appealing or aversive, preferentially capture exogenous attention due to their evolutionary significance. This study assessed whether such capacity persists at low contrast levels, where stimuli are minimally perceived. To this end, we recorded behavioral and electrophysiological (event-related potentials, ERPs) indices of attentional capture from 38 participants who were exposed to negative, neutral, and positive scenes, each presented at four distinct contrast levels. These contrast levels had previously resulted in a correct recognition rate of 49%, 52%, 58%, and 66% (chance = 50%) in a previous sample of 144 participants. Participants were presented with these scenes as distractors while simultaneously performing a perceptual task involving line orientation discrimination. ERP results revealed an emotional effect persistent across all contrast levels. Specifically, occipito-parietal P1 (88-119 ms) was larger for negative than for positive distractors, more intensely for the lowest contrast, while in a broadly spatially distributed N2 component, positive distractors elicited larger amplitudes relative to both negative (213-354 ms) and neutral (213-525 ms) images. While emotional valence did not influence behavioural measures, overall performance deteriorated as contrast increased. These findings suggest stimuli captured exogenous attention, and reinforce the advantage of emotional distractors in accessing neural processing automatically and highlight the existence of a temporal negativity bias. Importantly, our novel findings emphasize the robustness of this pattern, present even under limited perceptual conditions.
Automated Emotion Recognition in text is a challenging application that has attracted significant interest. This paper addresses the significant need to study recently-introduced text corpora labeled for emotion recognition tasks. In this paper, we detail and analyze 30 text corpora introduced since 2018, offering insights into their sources, languages, emotion labels, annotation methodologies, availability, size, and other characteristics. We also summarize previous models and results on emotion recognition using the corpora in our study, and share recent events such as shared tasks and other resources such as lexicons. Finally, we offer a discussion of related practices and challenges. Our aim is for this paper and the accompanying online repository to function as a comprehensive resource, offering researchers a centralized hub for accessing related links, information, comparisons, and more, while also educating the research community on current practices for data collection, annotation, and usage in emotion recognition.
In education, it is important to have good communication and interaction between educators and learners to promote a conducive learning environment. However, this is rather difficult for the children with motor impairments, such as children with Cerebral Palsy and Autism. Their learning problems arise due to their motor impairment coupled with speech and intellectual impairments. As a result, children with motor disabilities require more time and attention in learning. To assist the children's learning, this chapter proposes an affective computer-mediated learning model which adapts to learners' emotions where it has an educator representation (i.e. a virtual tutor) to deliver the learning materials and interact with a child in one-to-one learning. The virtual tutor communicates with the child by responding to his/her facial expressions. Post-intervention experiments were carried out to evaluate the performance of the affective computer-mediated learning model. The overall results showed that the proposed affective learning model is able to assist the children's learning.
This innovation project aims to correct the difficulties of students of the Degree in Musicology to use musical analysis tools. It is oriented towards the curricular competences of the subject Music and Thought in the Age of Enlightenment (18th century). This requires analytical work on the Central European tonal music repertoire in connection with the currents of style and thought of the time. According to the principle of Topic theory, a series of didactic strategies have been developed in order to connect the emotional experience of the student with the meaning of musical topics.
Recent work on natural categories suggests a framework for conceptualizing people's knowledge about emotions. Categories of natural objects or events, including emotions, are formed as a result of repeated experiences and become organized around prototypes (Rosch, 1978); the interrelated set of emotion categories becomes organized within an abstract-to-concrete hierarchy. At the basic level of the emotion hierarchy one finds the handful of concepts (love, joy, anger, sadness, fear, and perhaps, surprise) most useful for making everyday distinctions among emotions, and these overlap substantially with the examples mentioned most readily when people are asked to name emotions (Fehr & Russell, 1984), with the emotions children learn to name first (Bretherton & Beeghly, 1982), and with what theorists have called basic or primary emotions. This article reports two studies, one exploring the hierarchical organization of emotion concepts and one specifying the prototypes, or scripts, of five basic emotions, and it shows how the prototype approach might be used in the future to investigate the processing of information about emotional events, cross-cultural differences in emotion concepts, and the development of emotion knowledge.
A slide-viewing paradigm measuring the tendency to communicate accurate nonverbal messages via spontaneous facial expressions and gestures was applied to 13 male and 11 female preschoolers (aged 4-6 yrs). Ss watched 16 emotionally loaded color slides while, unknown to them, their mothers viewed their reactions via TV. Ss' skin conductance (SC) was monitored during the experiment, and they had been rated by 2 teachers on a new scale of affect expression developed from H. E. Jones's (1935) externalizer/internalizer distinction. High communication accuracy was associated with low SC responding. Rated expressiveness was associated with high communication accuracy and low SC responding. Sex differences appeared in the pattern of relations between the affect expression scale and the measures of communication accuracy and SC response. Theoretical implications are discussed. (17 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).
This paper uses a theory of the emotions to motivate a semantic analysis of English words referring to emotions. The theory assumes that emotions have a two-fold communicative function, both externally amongst members of the species, and internally within the brain so as to bypass complex inferences. It implies that there is a small number of basic signals that can set up characteristic emotional modes within the organism, roughly corresponding to happiness, sadness, fear, anger, and disgust. In human beings, these modes can be modulated by the propositional content of the cognitive evaluation that caused the emotion signal, or else, if this content fails to impinge on consciousness, these modes can be experienced as emotions that have occurred for no apparent reason. According to this “communicative” theory, there should be a set of terms that refer to basic emotions, and these terms should have no internal semantics, since they cannot be analysed into anything more basic, such as a prototype or a set of semantic features. Other terms should refer to states that combine a basic emotion with a propositional content. Finally, the theory implies that any emotional term should devolve upon one of the five basic emotion modes, or some subset of them, and that there will be no need to invoke any other emotional states. These predictions were borne out by the semantic analysis of 590 emotion words.
Using a theory of emotional understanding, the basis for distinguishing among happiness, anger, and sadness was investigated. Three and six-year-old children and adults predicted and explained people's emotional responses to different types of events. The events varied as to whether a person's goal was to attain or to avoid a state, whether the goal was achieved or not, who or what was responsible for success or failure, and whether the outcome was intentional or accidental. For all groups, the attainment and maintenance of goals was the primary focus of explanations for emotions and for the plans that followed emotions. A distinct set of features was used to infer and explain happiness as opposed to anger and sadness. Happiness was elicited by goal success and was followed by plans to maintain or enjoy current goal states. Anger and sadness were elicited by goal failure and were followed by plans to reinstate, replace, or forfeit goals. Anger occurred more frequently than sadness when an aversive rather than a loss state occurred, when an animate agent rather than a natural event caused a negative outcome, and when attention was focused on the cause rather than the consequence of goal failure. Two dimensions associated with anger changed as a function of age. First grade children, and adults were more likely than preschool children to predict anger in response to intentional harm, and their explanations for anger were more likely to refer to the agent or cause of goal failure. For all age groups, however, the majority of subjects responded to aversive situations with anger responses, independent of the causal conditions that produced the aversive state. The results therefore indicate that anger can be produced without intentional harm, but that intentional harm becomes an important dimension in attributing anger, especially as a function of development.
Three studies tested whether infant facial expressions selected to fit Max formulas (C. E. Izard, 1983) for discrete emotions are recognizable signals of those emotions. Forced-choice emotion judgments (Study 1) and emotion ratings (Study 2) by naive Ss fit Max predictions for slides of infant joy, interest, surprise, and distress, but Max fear, anger, sadness, and disgust expressions in infants were judged as distress or as emotion blends in both studies. Ratings of adult facial expressions (Study 2 only) fit a priori classifications. In Study 3, the facial muscle components of faces shown in Studies 1 and 2 were coded with the Facial Action Coding System (FACS; P. Ekman and W. V. Friesen, 1978) and Baby FACS (H. Oster and D. Rosenstein, in press). Only 3 of 19 Max-specified expressions of discrete negative emotions in infants fit adult prototypes. Results indicate that negative affect expressions are not fully differentiated in infants and that empirical studies of infant facial expressions are needed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Presents a theory that describes motivation and emotion as different aspects of a single process in which emotion involves the readout of motivational potential inherent in hierarchically organized primary motivational/emotional systems (primes). This theory involves an integrated way of thinking about emotion and motivation in their various physiological, expressive, and cognitive aspects. The most basic readout, Emotion I, involves adaptive-homeostatic functions. In species where communication about the state of certain primes became important, Emotion II, involving their outward expression, evolved. With cognition, a 3rd type of readout evolved, Emotion III, involving the direct experience of certain primes. A model of the interaction between primes and cognition is presented, and the unique role of language in human motivation-emotion is discussed. (4½ p ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
35 right-handed White females (18–35 yrs) viewed positive and stress-inducing motion picture films and then reported on their subjective experience. Spontaneous facial expressions provided accurate information about more specific aspects of emotional experience than just the pleasant vs unpleasant distinction. The facial action coding system (P. Ekman and W. V. Friesen, 1978) isolated a particular type of smile that was related to differences in reported happiness between Ss who showed this action and Ss who did not, to the intensity of happiness, and to which of 2 happy experiences was reported as happiest. Ss who showed a set of facial actions hypothesized to be signs of various negative affects reported experiencing more negative emotion than Ss who did not show these actions. How much these facial actions were shown was related to the reported intensity of negative affect. Specific facial actions associated with the experience of disgust are identified. (38 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
in our discussion of emotion and dysfunction, we have intimated that emotions are instructive about persons because both emotions and the personality are organized around the problem of surviving, getting along, and flourishing over the life course
begin by addressing the question of what an emotion is / describe our own [the authors'] recent work directed at illuminating what we see as one of the important issues in emotion theory—the role of cognitive appraisal
embed this work in a general model of emotion, which identifies the key variables and processes within a systems framework emphasizing person-environment relationships and cognitive mediation
illustrate how emotion theory makes firm contact with a variety of topics currently being pursued across diverse psychological disciplines, especially personality and social psychology
the adaptational problem and the evolution of emotion / appraisal theory / personality, society, and biology in emotion (PsycINFO Database Record (c) 2012 APA, all rights reserved)
A theory is proposed that emotions are cognitively based states which co-ordinate quasi-autonomous processes in the nervous system. Emotions provide a biological solution to certain problems of transition between plans, in systems with multiple goals. Their function is to accomplish and maintain these transitions, and to communicate them to ourselves and others. Transitions occur at significant junctures of plans when the evaluation of success in a plan changes. Complex emotions are derived from a small number of basic emotions and arise at junctures of social plans.
We first review the main points in the dispute about whether emotion is primary and independent of cognition (Zajonc), or secondary and always dependent upon cognition (Lazarus), and suggest that the dispute is largely one of definition. Because definitional disputes seldom clarify substantive, theoretical points, we suggest a variety of questions regarding cognition-emotion interaction. To stimulate discussion of these issues, we propose a componential model in which emotions are seen to develop from simpler, reflex-like forms (“wired-in” sensory-motor processes) to complex cognitive-emotional patterns that result from the participation of at least two distinct levels of memory and information processing, a schematic and a conceptual level. These systems are typically activated by a continuous stimulus check process which evaluates five environment-organism attributes: novelty; pleasantness; goal conductiveness; coping potential; and consistency with social norms and self-relevant values. Questions about the relationship of cognition to emotion, and how two initially independent systems become inseparably interrelated, are transformed when viewed within the context of the dynamic, multilevel emotion processing system.
The nature and degree of cross-cultural variability in emotional behaviour is a question of relevance to a broad spectrum of the behavioural science community. The literature in this area has been dominated by cross-cultural studies of facial expressions, a few studies of affective language, and single-cultural clinical and ethnographic accounts of affective behaviour. The present paper differs from most of the literature by reporting some of the results of a cross-cultural study of the antecedents to emotional experience.
• It was recently proposed that the affective components of language, encompassing prosody and emotional gesturing, are a dominant function of the right hemisphere, and that their functional-anatomic organization in the right hemisphere mirrors that of propositional language in the left hemisphere. Ten righthanded patients with focal lesions of the right hemisphere and disorders of affective language are described. Observations were made about each patient's spontaneous prosody, prosodic repetition, prosodic comprehension, and comprehension of emotional gesturing. Using this particular examination strategy, which is derived from the usual bedside approach to aphasic disorders, the organization of affective language in the right hemisphere does mirror the organization of propositional language in the left hemisphere. Furthermore, the disorders of affective language seem to be classifiable in the same manner as the aphasias. Thus, the term "aprosodia," preceded by specific modifiers such as motor, global, transcortical sensory, etc, seems appropriate when classifying the various disorders of affective language that occur following right-hemisphere damage. The relationships between affect, mood, pathologic laughing and crying, and depression are also discussed.
Forty-three subjects were stimulated in the laboratory to "fear" and "anger," during which the following physiological reactions were recorded: (1) heart rate, (2) ballistocardiogram, (3) respiration rate, (4) face temperature, (5) hand temperature, (6) skin conductance, and (7) integrated muscle potential. The scores used were the maximum rise and maximum fall from the preceding resting level and the number of responses of a critical value per unit time. Of the 14 scores thus obtained, 7 showed significant discrimination between anger and fear. Diastolic blood pressure rises, heart rate falls, number of rises in skin conductance, and muscle potential increases, were greater for anger than for fear, whereas skin conductance increases, number of muscle potential increases, and respiration rate increases were greater for fear than for anger. Profile difference scores, computed from appropriate combinations of these differences, were found to be greater than zero in 42 of the 43 cases and to have a mean which deviated very significantly from zero, which rejects the null hypothesis that there is no difference in physiological reaction between anger and fear. The patterns obtained for anger and fear argue against the Arnold proposal that anger is a strong reaction of both the sympathetic and parasympathetic branches of the autonomic nervous systems, whereas fear is but a sympathetic reaction. Another finding was the very low correlations among the physiological reactions and the significantly higher intercorrelations for anger than for fear, which was interpreted as indicating greater physiological integration during anger. Between-subject variance was significantly greater than within-subject variance, which supports the findings of Lacey and Malmo that there is considerable specificity in physiological response patterns. The physiological response patterns of anger were suggested as being similar to those produced by injections of epinephrine and nor-epinephrine combined, and those of fear as being similar to injections of epinephrine. Copyright (C) 1953 by American Psychosomatic Society
Despite the burgeoning literature using facial electromyography (EMG) to study cognitive and emotional processes, the psychometric properties of facial EMG measurement have received little attention. Two experiments were conducted to assess the reliability and validity of facial EMG as a measure of specific facial actions. In Experiment 1, two recording sites in the brow region were compared for their ability to differentiate facial actions hypothesized to be due to the activation of the corrugator supercilii from facial actions presumed to be due to the activation of proximate muscles (e.g. depressor supercilii, procerus, frontalis, levator labii superioris alaeque nasi, orbicularis oculi), and four sites in the infraorbital triangle were compared for their ability to differentiate facial actions hypothesized to be due to the activation of the zygomaticus major from facial actions presumed to be due the activation of proximate muscles (e.g. zygomaticus minor, risorius, buccinator, orbicularis oculi, orbicularis oris). Fifteen subjects were instructed to pose a series of facial actions while EMG activity was sampled simultaneously at all sites. In Experiment 2, 5 subjects returned to the laboratory for a more extensive investigation of surface EMG activity over the zygomaticus major muscle region. The results of this experiment confirmed the findings of Experiment 1. Overall, the results demonstrate that certain recording sites located over specific facial muscle regions are more sensitive and valid indices of particular facial actions than other nearby sites.
Thirty American subjects accurately identified emotions from 96 situations which American and Malay informants stated to be antecedent to specific emotions. These results are considered in terms of the proposition that the underlying meanings of antecedent events are the stimuli for the experience of emotion, and that these meanings can be inferred across cultural boundaries.
The evidence on universals in facial expression of emotion, renewed controversy about that evidence, and new findings on cultural differences are reviewed. New findings on the capability for voluntarily made facial expressions to generate changes in both autonomic and central nervous system activity are discussed, and possible mechanisms by which this could occur are outlined. Finally, new work which has identified how to distinguish the smile of enjoyment from other types of smiling is described.
A theory specifying how appraisals of a situation determine one's emotional responses (Roseman, 1979) was subjected to an experimental test. According to the theory, particular combinations of 5 appraisals determine which of 13 qualitatively different emotions will be experienced in any given situation. The appraisals are: motivational state (rewarding/punishing), situational state (presendabsent), probability (certaiduncertain), legitimacy (positivehegative outcome deserved), and causal agency (circumstanced other person/self). The emotions whose occurrence they determine are joy, relief, hope, liking (“warmth-friendliness”), pride, distress, sorrow, fear, frustration, disliking (“coolness-unfriendliness”), anger, regret, and guilt. In the experiment, 120 college students read brief stories in which these appraisals were manipulated, and rated the intensities of various emotions felt by story protagonists. Results showed that each appraisal had a significant effect upon emotions, and that the particular combinations of appraisals specified by the theory predict the relative intensities of particular emotions, across a wide variety of situations. Theoretical predictions were more clearly supported for appraisals of motivational state, situational state and probability than for appraisals of legitimacy and agency. Results provide significant support for the theory, and suggest that it be subjected to further testing and development. Possible modifications in the theory are also discussed.
[reviews] cross-cultural evidence for the universality of emotional expression in the face / other facets of emotional expression in the face reviewed in the current chapter are: the neuromuscular substrates of facial behavior, phylogenetic bases of human facial action
address[es] broader issues such as the relationship of encoding and decoding skills, gender differences, the role of the different nonverbal channels in the expression of emotion and the role of peripheral feedback in the experience of emotion (PsycINFO Database Record (c) 2012 APA, all rights reserved)
636 university students from France, West Germany, Italy, Switzerland, and the UK completed a questionnaire (in their native language) asking them to describe events that had evoked in them the following emotions: joy/happiness/pleasure, sadness/sorrow/grief, anger/bad temper/rage, and fear/fright/terror. Results indicate that there were systematic individual as well as cross-cultural differences in Ss' experiences with the intensity of each emotion, the amount of control Ss had, the duration of the emotions, the amount of verbalization while experiencing an emotion, and the antecedents that precipitated each emotion. The ongoing work of this research group is concerned with a refinement of the methodology, a replication of the present findings, and a more systematic evaluation of the data in relation to concepts of culture rather than simply of national boundaries. (29 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
theoretical approaches discussed in this paper . . . explain the patterns of situation evaluation preceding emotional responses / "cognitive emotion theories"
highlight the emotion-antecedent appraisal process and use the evaluation criteria to explain the differentiation of emotion
categorization of the different appraisal factors / change in state of affairs / type of stimulus event / consequences of event / relationship of event to concerns and goals / consistency of consequences with expectation / causation of event / potential to cope with consequences / relation of event to external and internal standards
major paradigms for this type of empirical investigation are described and some representative studies are reviewed
comprehensive prediction table for future empirical investigations, based on theoretical considerations, as well as on the pattern of empirical findings reviewed here, will be suggested (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Presents data from cross-cultural, cross-species, and ontogenetic studies of expressive patterns, particularly the "eyebrow flash," head shaking, and face hiding. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
We obtained the first evidence of a facial expression unique to contempt. Contrary to our prediction, this contempt expression was not culture-specific but was recognized by people in Estonia S.S.R., Germany, Greece, Hong Kong, Italy, Japan, Scotland, Turkey, the United States, and West Sumatra. Pan-cultural agreement about the contempt expression was as high as has been found previously for other emotions.
A recent study of the effect of context in the judgment of contempt facial expression (Russell, 1991) was flawed by several confusions about what constitutes context. We argue that the context used should have ecological validity, through the use of many, rather than a few, facial expressions, which are spontaneous rather than posed, and which are judged by carefully selected judgment tasks, using clearly defined or well-understood emotional terms. The confusion in Russell's work between accuracy studies and agreement studies is also addressed.
Two experiments replicated Ekman and Friesen''s finding of an expression that signals contempt across cultures. The subjects, from West Sumatra, Indonesia, were members of a culture that differs in a number of ways from Western cultures. In one experiment the subjects judged photographs of Japanese and American faces, both males and females, which showed many different emotions. There was very high agreement about which expressions signaled contempt in preference to anger, disgust, happiness, sadness, fear, or surprise. In a second experiment the Indonesian subjects judged expressions shown by members of their own culture, and again there was very high agreement about which expression signals contempt.
Izard and Haynes question our findings and claims for disovery because they did not consider the difference between a one-to-one and one-to-many relationship between a sign (the facial expression) and what it signifies (a message about emotion). Clarifying this matter not only shows that the disagreement between us is more apparent than real, but more importantly highlights what remains to be discovered about which emotional states are signaled by which facial expressions.
The claim of Ekman and Friesen (1986, A New Pan- Cultural Facial Expression of Emotion,Motivation and Emotion, 10, 159–168) that they have found the first empirical support for the existence of a pancultural expression of contempt is challenged on three grounds. First, the claim that no one else had ever attempted to describe an expression unique to contempt in any culture neglects a tradition of research dating back to Darwin. Second, the data presented by Ekman and Friesen were derived using stimuli that are ambiguous representations of their intended expressions. Finally, there are earlier data for the universality of contempt expressions. Ekman and Friesen''s contempt expression may best be viewed as a learned modification of a prototypical expression evolved from the infrahuman snarl.
Theoretically based distinctions linked to measurable differences in appearance are described for three smiles: felt smiles (spontaneous expressions of positive emotion); false smiles (deliberate attempts to appear as if positive emotion is felt when it isn''t); and, miserable smiles (acknowledgements of feeling miserable but not intending to do much about it). Preliminary evidence supports some of the hypotheses about how these three kinds of smile differ.
Ekman and Friesen (1986) claimed to have discovered a facial expression, a unilateral lip curl, universally recognized as conveying contempt. Their conclusion was based on a series of labeling studies, all of which relied on one response measure—subjects choosing one label from a small, preselected list. This article reports two studies on the question of whether their result can be replicated with other response measures. In one study, subjects were allowed to respond with any emotion label they wanted; in the second, subjects were asked to make quantitative ratings on six emotion scales. Neither method suggested contempt as subjects' interpretation of the unilateral lip curl.
A procedure has been developed for measuring visibly different facial movements. The Facial Action Code was derived from an analysis of the anatomical basis of facial movement. The method can be used to describe any facial movement (observed in photographs, motion picture film or videotape) in terms of anatomically based action units. The development of the method is explained, contrasting it to other methods of measuring facial behavior. An example of how facial behavior is measured is provided, and ideas about research applications are discussed.