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Anegayuda, Yugen Ghifari, Rifani Alya Araminta, and Hanna Christina Uranus. "Development of a Booklet for Introduction to Types of Emotions in Preschool Children." JISIP (Jurnal Ilmu Sosial dan Pendidikan) 8, no. 3 (2024): 1629. http://dx.doi.org/10.58258/jisip.v8i3.7072.
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This study aims to develop an emotion recognition booklet for preschoolers based on Paul Ekman's (1972) basic emotion types. This research uses the Research & Development (R&D) method with ADDIE instructional design. Validation by experts showed that the booklet is 100% very valid and feasible to use to support emotional learning in early childhood in preschool, Before the use of the booklet, children only recognize some basic emotions such as angry and sad. After using the booklet, they can identify six basic emotions and connect the expression of emotions with triggers in daily life. The booklet is designed with simplified sentences and attractive visuals, using an interactive approach.
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Silitonga, R. H. Yanti, Dadan Dasari, and Jarnawi Afgani Dahlan. "Exploration of high school students' sentiments and emotions towards mathematics: Linked to learning outcomes." Jurnal Gantang 9, no. 2 (2024): 215–28. https://doi.org/10.31629/jg.v9i2.7456.
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Mathematics research often focuses only on students' learning outcomes without considering their emotional aspects. This study aims to describe the tendency of students' sentiment toward mathematics in general and partially based on mathematics learning outcome groups, namely high, medium, and low. In addition, a mood analysis was conducted using Ekman's Basic Emotion classification. Data collection techniques are questionnaires and documentation. The questionnaire contains open questions about students' opinions on mathematics and closed to queries for student demographics. Documentation is done by collecting test scores from student grade books. This study used a descriptive method with data in the form of 72 comments from grade XI high school students in Bandung City, which were analyzed using the Orange Application Sentiment Analysis. The results of the study showed that (1) student sentiment was generally dominated by positive sentiment at 72.22%, (2) positive sentiment also dominated the groups of students with high, medium, and low learning outcomes, with a percentage of more than 68%, and (3) the results of the classification of emotions based on Ekman's Basic Emotion indicated that "joy" was the most dominant emotion, while "anger" had the lowest frequency of occurrence. This study provides new insights regarding students' emotional aspects in mathematics learning, which can be used to improve teaching strategies.
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Silitonga, R. H. Yanti, Dadan Dasari, and Jarnawi Afgani Dahlan. "Exploration of high school students' sentiments and emotions towards mathematics: Linked to learning outcomes." Jurnal Gantang 9, no. 2 (2024): 215–28. https://doi.org/10.31629/jg.v9i2.6953.
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Mathematics research often focuses only on students' learning outcomes without considering their emotional aspects. This study aims to describe the tendency of students' sentiment toward mathematics in general and partially based on mathematics learning outcome groups, namely high, medium, and low. In addition, a mood analysis was conducted using Ekman's Basic Emotion classification. Data collection techniques are questionnaires and documentation. The questionnaire contains open questions about students' opinions on mathematics and closed to queries for student demographics. Documentation is done by collecting test scores from student grade books. This study used a descriptive method with data in the form of 72 comments from grade XI high school students in Bandung City, which were analyzed using the Orange Application Sentiment Analysis. The results of the study showed that (1) student sentiment was generally dominated by positive sentiment at 72.22%, (2) positive sentiment also dominated the groups of students with high, medium, and low learning outcomes, with a percentage of more than 68%, and (3) the results of the classification of emotions based on Ekman's Basic Emotion indicated that "joy" was the most dominant emotion, while "anger" had the lowest frequency of occurrence. This study provides new insights regarding students' emotional aspects in mathematics learning, which can be used to improve teaching strategies.
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Singh, Ankit. "Realtime Facial Emotion Detection." International Journal for Research in Applied Science and Engineering Technology 12, no. 3 (2024): 3226–29. http://dx.doi.org/10.22214/ijraset.2024.59630.
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Abstract: A crucial component of communication is facial emotion through facial expression. This makes the problem of evaluating human emotions via computer systems an intriguing one that has attracted increasing amounts of attention in the past few decades. The main connection is that facial expression recognition could be used in a variety of industries, including virtual reality, video games, HCI, and customer satisfaction analysis. Face detection, facial feature extraction, and expression categorization are the final three basic steps in the emotions determination (recognition process). The Russell circular approach, which has up to 24 emotional expressions, and Plutchik's Wheel of Emotions are two other categorization schemes that are frequently encountered. Ekman's classification, which has six emotional expressions (or seven, if it is a neutral expression), is the most common.
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Sabini, John, and Maury Silver. "Ekman's basic emotions: Why not love and jealousy?" Cognition & Emotion 19, no. 5 (2005): 693–712. http://dx.doi.org/10.1080/02699930441000481.
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Wahyudi, Aditio, Arief Tirtana, and Lady Diana Langoy. "Analysis of Gojek's Brand Perception Utilizing Twitter Hashtag: Sentiment Analysis Using Ekman's Classification." Open Access Indonesia Journal of Social Sciences 6, no. 2 (2023): 927–35. http://dx.doi.org/10.37275/oaijss.v6i2.153.
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Advertisers constantly try to use different communication channels to approach consumers more effectively and promptly and increase their products' visibility and attractiveness. Gojek, an Indonesian ride-hailing and delivery company, uses hashtags as part of its marketing strategy on social media platforms such as Twitter and Instagram. This research aimed to analyze Gojek's brand perception using the Twitter hashtag. This research uses descriptive analysis and sentiment analysis using Ekman's classification of emotional expression algorithm. This research analyzed 813 tweets containing hashtags related to Gojek, an Indonesian ride-hailing and delivery company, including #AmanBersamaGojek, #Cerdikiawan, #JalanTerus, #PastiAdaJalan, and #SebelumGojek, to understand the sentiment and emotional tone of the tweets. Using Ekman's classification method for identifying and categorizing emotional expressions, the analysis found that the tweets were predominantly positive in sentiment, with surprise and joy being the most frequently expressed emotions. However, the research also identified a range of other emotions expressed in the tweets, including fear, sadness, disgust, and anger, indicating that Twitter users may have more complex and nuanced attitudes toward Gojek and its hashtags. In conclusion, Gojek may consider conducting additional research and implementing strategies to address negative emotions and better engage with its audience on social media to improve its brand perception on Twitter.
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Widyastuti, Widyastuti, Dadang Dasari, and Sri Hastuti Noer. "“Apa yang Siswa Pikirkan Tentang Matematika?” Analisis Sentimen pada Siswa Kelas Tinggi Sekolah Dasar." Jurnal Pendidikan Matematika Universitas Lampung 12, no. 4 (2024): 252–65. https://doi.org/10.23960/mtk/v12i4.pp252-265.
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The purpose of this study was to describe a sentiment model for elementary school students' comments on mathematics. Respondents in this study were 286 elementary school students in seven elementary schools in Bandar Lampung. Sentiment data were obtained through student comments that were collected in May-June 2024. Data analysis used sentiment analysis and mood analysis based on student comment texts carried out using Ekman's Basic Emotions classification. The analysis was carried out through Orange software using Corpus analysis, sentiment analysis, topic modeling, and also tweet profiler. The results of the analysis revealed that: i) the sentiment of elementary school students was dominated by positive sentiment (percentage achievement of 50%), with the three most keywords expressed in students' textual comments about mathematics were "fun", "difficult", "hard"; ii) the sentiment displayed by grade 5 and grade 6 students was dominated by positive sentiment while grade 4 students predominantly caused negative sentiment; and iii) the results of Ekman's Basic Emotions classification showed that "Joy" was the most dominant emotion felt by students in their textual comments about mathematics, while "fear" was the emotion with the least occurrence in students' textual comments about mathematics. The implications of the finding for the model of positive sentiment of elementary school students towards mathematics which can be used as a basis for selecting research interventions and mathematics learning strategies/methods that are more appropriate for elementary school students.
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PRAMESWARI, SALWA, INDAH AGUSTIA, and YANTI ROSALINAH. "THE EMOTIONS ANALYSIS OF THE MAIN CHARACTER “SAMIRA” IN MOVIE A QUIET PLACE: DAY ONE." GANEC SWARA 18, no. 4 (2024): 2228. https://doi.org/10.35327/gara.v18i4.1111.
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The purpose of this study is to examine and understand the feelings experienced by Samira, the main character from Michael Sarnoski’s movie “A Quiet Place Day One”. The purpose of this study is to find out and investigate Samira's emotional responses to the various circumstances she experiences, by identifying a wide range of emotions. The movie “A Quiet Place Day One” has 12 data found. Data was collected using the book 'Emotions revealed' from Ekman's theory. The complex structure of Samira's emotions and how they affect the film will be emphasized in the conclusion of the research. The two most common survival techniques used by Samira, the protagonist in the movie, are following her instincts and staying strong in the face of adversity. This study may shed light on how the character handles challenging circumstances.
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Pretsch, Juergen, Ekaterina Pretsch, and Michael Fuchs. "Artificial Creativity – Early Analyses of LLMs’ Creative Approaches." European Journal of Social Science Education and Research 11, no. 1 (2024): 140–66. https://doi.org/10.26417/qagjr841.
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This study explores AI creativity through a two-pronged experiment: ChatGPT for language processing and MidJourney for text-to-image synthesis. Both models focused on expressing Ekman's six basic emotions. By manipulating ChatGPT's 'temperature' to vary linguistic creativity and using these outputs to guide MidJourney's image creation, the research examines the nuanced capabilities of AI in generating emotionally resonant artworks and linguistically complex prompts. The study's findings highlight two significant contributions of AI to creative domains: firstly, AI's ability to evoke specific emotions in viewers through art, effectively bridging the gap between synthetic cognition and human emotion; and secondly, AI's development of unique artistic styles, a result of assimilating and reinterpreting diverse artistic influences. These insights not only broaden our understanding of AI's creative capabilities but also point towards its potential to significantly enrich the artistic landscape.
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Parkinson, Brian. "Do Facial Movements Express Emotions or Communicate Motives?" Personality and Social Psychology Review 9, no. 4 (2005): 278–311. http://dx.doi.org/10.1207/s15327957pspr0904_1.
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This article addresses the debate between emotion-expression and motive-communication approaches to facial movements, focusing on Ekman's (1972) and Fridlund's (1994) contrasting models and their historical antecedents. Available evidence suggests that the presence of others either reduces or increases facial responses, depending on the quality and strength of the emotional manipulation and on the nature of the relationship between interactants. Although both display rules and social motives provide viable explanations of audience “inhibition ” effects, some audience facilitation effects are less easily accommodated within an emotion-expression perspective. In particular emotion is not a sufficient condition for a corresponding “expression,” even discounting explicit regulation, and, apparently, “spontaneous ”facial movements may be facilitated by the presence of others. Further, there is no direct evidence that any particular facial movement provides an unambiguous expression of a specific emotion. However, information communicated by facial movements is not necessarily extrinsic to emotion. Facial movements not only transmit emotion-relevant information but also contribute to ongoing processes of emotional action in accordance with pragmatic theories.
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Arous, A., J. Mrizak, R. Trabelsi, A. Aissa, H. Ben Ammar, and Z. El Hechmi. "Clinical symptomatology and facial emotion recognition in schizophrenia: Which relationship?" European Psychiatry 33, S1 (2016): S96. http://dx.doi.org/10.1016/j.eurpsy.2016.01.066.
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IntroductionPatients with schizophrenia show impairments in social cognitive abilities, such as recognizing facial emotions. However, the relationships between specific deficits of emotion recognition and with clusters of psychotic remain unclear.ObjectivesTo explore whether facial emotion recognition was associated with severity of symptoms and to which presentation of psychotic symptoms.MethodsFacial emotion recognition (FER) were evaluated in 58 patients with stable schizophrenia with a newly validated FER task constructed from photographs of the face of a famous Tunisian actress representing the Ekman's six basic emotions (happiness, anger, disgust, sadness, fear, and surprise). Symptomatology evaluation comprised the Positive and Negative Syndrome Scale (PANSS), the Calgary Depression Scale for Schizophrenia (CDSS) and the Clinical Global Impressions Scale Improvement and severity (CGI).ResultsPatients who failed to identify anger had significantly higher scores in hyperactivity item (P < 0.0001). The patients who had a difficulty to identify sadness had more grandiosity (P ≤ 0.002). The impairment in happiness recognition was correlated with hallucination (P = 0.007) and delusion (P = 0.024) items. Incapacity to identify fear was associated to lack of judgment and insight (P = 0.004).ConclusionsDeficits in recognition of specific facial emotions may reflect severity of psychiatric symptoms. They may be related to specific clusters of psychotic symptoms, which need to be confirmed in further studies.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Mrizak, J., A. Arous, R. Trabelsi, A. Aissa, H. Ben Ammar, and Z. El Hechmi. "The association between childhood trauma and facial emotion recognition in patients with stable schizophrenia." European Psychiatry 33, S1 (2016): S372. http://dx.doi.org/10.1016/j.eurpsy.2016.01.1334.
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IntroductionThe impairment of facial emotion recognition (FER) among patients with schizophrenia (SCZ) is a significant feature of the illness. Childhood trauma (CT) is reported with a high prevalence in SCZ and is considered one of its risk factors.ObjectivesTo investigate the relationship between FER and CT in SCZ.MethodsFifty-eight outpatients with stable SCZ completed the Childhood Trauma Questionnaire retrospectively assessing five types of childhood trauma (emotional, physical and sexual abuse, and emotional and physical neglect). They also completed a newly developed and validated FER task constructed from photographs of the face of a famous Tunisian actress and evaluating the ability to correctly identify Ekman's six basic facial emotions (happiness, sadness, anger, disgust, fear and surprise).ResultsPatients with higher scores of CT performed significantly worse in FER task. Our results suggest that the presence of sexual abuse is specifically correlated to a poor identification of anger (P = 0.02) and disgust (P = 0.03) while the presence of emotional abuse and physical neglect are correlated to a poor identification of happiness and sadness.ConclusionsCT may represent one of the causes of the FER deficits in schizophrenia. Further studies are necessary to confirm the link between specific kinds of childhood trauma and deficits in the recognition of discrete emotions.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Norouzian, Mahtab, Vahid Nejati, and Fariborz Bagheri. "Investigation of the Evolution of Attention Abilities, and Emotional Recognition in Children with Normal and Abnormal Development." Applied Family Therapy Journal 4, no. 3 (2023): 470–83. http://dx.doi.org/10.61838/kman.aftj.4.3.29.
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Aim: The purpose of the present study was to investigate the evolution of attention and emotional recognition abilities in preschool and elementary school children with normal and abnormal development. Methods: The current research was a descriptive and comparative study. The research population included all hyperactive children under treatment at Mashavah Rouhana and Tivat centers and preschool and primary school children in schools in District 1, 2 and 3 of Tehran in the academic year of 2017-2018. Among these children, 410 children were selected using a multi-stage random sampling method. To collect data, the continuous performance test of Rossold et al. (1956) and Ekman's emotion recognition test (2007) were used. To analyze the data, one-way analysis of variance and Tukey's post hoc test were used by SPSS-22. Results: The results of the analysis of variance showed that the participants in two groups, normal and hyperactive, have different ability to pay attention and recognize emotions, and this difference is significant in all components at the 0.001 level. Conclusion: According to the results of the present study, attention and emotional recognition in children play an important role in improving their social communication and academic performance. Therefore, examining and strengthening it in primary school ages around 4 to 8 years old and even up to 12 years old when the transformation of the frontal parts is complete, plays an important role in academic success.
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SÖDERSTRÖM, ULRIK, and HAIBO LI. "REPRESENTATION BOUND FOR HUMAN FACIAL MIMIC WITH THE AID OF PRINCIPAL COMPONENT ANALYSIS." International Journal of Image and Graphics 10, no. 03 (2010): 343–63. http://dx.doi.org/10.1142/s0219467810003810.
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In this paper, we examine how much information is needed to represent the facial mimic, based on Paul Ekman's assumption that the facial mimic can be represented with a few basic emotions. Principal component analysis is used to compact the important facial expressions. Theoretical bounds for facial mimic representation are presented both for using a certain number of principal components and a certain number of bits. When 10 principal components are used to reconstruct color image video at a resolution of 240 × 176 pixels the representation bound is on average 36.8 dB, measured in peak signal-to-noise ratio. Practical confirmation of the theoretical bounds is demonstrated. Quantization of projection coefficients affects the representation, but a quantization with approximately 7-8 bits is found to match an exact representation, measured in mean square error.
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Arous, A., J. Mrizak, R. Trabelsi, A. Aissa, H. Ben Ammar, and Z. El Hechmi. "Are neurocognition and facial emotion recognition related in schizophrenia?" European Psychiatry 33, S1 (2016): S366. http://dx.doi.org/10.1016/j.eurpsy.2016.01.1313.
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IntroductionPatients with schizophrenia (SCZ) show impairments in many social cognition domains including facial emotion recognition (FER). The existence of a relationship association between FER and neurcognitive functioning (NF) remains uncertain.ObjectivesTo investigate the association between ToM functioning and neurocognitive functioning in SCZ.MethodsFER was evaluated in 58 patients with stable schizophrenia with a newly validated FER task constructed from photographs of the face of a famous Tunisian actress representing the Ekman's six basic emotions. They also completed a neurocognitive battery comprising the following tests: the Hopkins Verbal Learning Test–Revised (HVLT-R), the Letter Digit Substitution Test (LDST), the Stroop Test (ST), the “Double Barrage” of Zazzo (DBZ), the Modified Card Sorting Test (MCST), Verbal Fluency (VF), the Trail Making Test-Part A (TMT-A) and the Digit Span (DS).ResultsPatients who performed better in the FER task had better performance in the VF task (P = 0.001) and in the immediate recall of the HVLT-R (P = 0.021). No correlations were found with the other neurocognitive tests.ConclusionsOur results suggest that FER represents an autonomous cognitive function which does not necessarily require good NF.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Johnson, John A., Joseph Carroll, Jonathan Gottschall, and Daniel Kruger. "Hierarchy in the Library: Egalitarian Dynamics in Victorian Novels." Evolutionary Psychology 6, no. 4 (2008): 147470490800600. http://dx.doi.org/10.1177/147470490800600414.
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The current research investigated the psychological differences between protagonists and antagonists in literature and the impact of these differences on readers. It was hypothesized that protagonists would embody cooperative motives and behaviors that are valued by egalitarian hunter-gatherers groups, whereas antagonists would demonstrate status-seeking and dominance behaviors that are stigmatized in such groups. This hypothesis was tested with an online questionnaire listing characters from 201 canonical British novels of the longer nineteenth century. 519 respondents generated 1470 protocols on 435 characters. Respondents identified the characters as protagonists, antagonists, or minor characters, judged the characters' motives according to human life history theory, rated the characters' traits according to the five-factor model of personality, and specified their own emotional responses to the characters on categories adapted from Ekman's seven basic emotions. As expected, antagonists are motivated almost exclusively by the desire for social dominance, their personality traits correspond to this motive, and they elicit strongly negative emotional responses from readers. Protagonists are oriented to cooperative and affiliative behavior and elicit positive emotional responses from readers. Novels therefore apparently enable readers to participate vicariously in an egalitarian social dynamic like that found in hunter-gatherer societies. We infer that agonistic structure in novels simulates social behaviors that fulfill an adaptive social function and perhaps stimulates impulses toward these behaviors in real life.
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Arous, A., J. Mrizak, R. Trabelsi, A. Aissa, H. Ben Ammar, and Z. El Hechmi. "How do social cognition dimensions relate to DSM-5 dimensions of psychosis?" European Psychiatry 33, S1 (2016): s241. http://dx.doi.org/10.1016/j.eurpsy.2016.01.607.
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IntroductionExisting research shows that individuals with schizophrenia (SCZ) show substantial deficits in social cognitive domains, including facial emotion recognition (FER), empathy, and Theory of Mind (ToM). Their exact relationship with the different dimensions included in the “Clinician- Rated Dimensions of Psychosis Symptom Severity” of the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) remains unexplored.ObjectivesTo investigate the relationship between different social cognition dimensions and the dimensions of psychosis included in the DSM-5.MethodsFifty-eight outpatients with stable SCZ completed the Intention-Inferencing Task (IIT), a non-verbal ToM task and the Questionnaire of Cognitive and Affective Empathy (QCAE). They also completed a newly developed and validated FER task constructed from photographs of the face of a famous Tunisian actress and evaluating the ability to correctly identify Ekman's six basic facial emotions. The clinician-rated dimensions of psychosis symptom severity was used to evaluate 8 dimensions of psychosis.ResultsThe patients presenting higher cognitive empathy capacities had less present abnormal psychomotor behaviour scores (P = 0.05). Higher levels of affective empathy were correlated to lower present delusions score (P = 0.037). Better scores in the IIT were correlated to less present negative scores (P = 0.013) and less impaired cognition scores (P = 0.009). FER task score didn’t correlated with any clinical dimension.ConclusionsOur results suggest the existence of specific relationships between social cognition dimensions and psychosis dimensions. Further studies are needed to confirm these relationships.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Merlina, Tina, Lia Maulia, and Rosaria Mita Amalia. "Verbal and Visual Expression of Emotions on Kaskus: a Semiotic Study." MIMBAR, Jurnal Sosial dan Pembangunan 29, no. 1 (2013): 85. http://dx.doi.org/10.29313/mimbar.v29i1.373.
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This research investigates the types of emoticons which occured on Kaskus. This is a qualitative research. The writer take the data from Kaskus, therefore it is a forum in the internet which has grown to be one of the most popular websites in Indonesia. To identify the types of Emotions on Kaskus, the writer analyzed the data using Ekman (2003) . From the discussions, there are verbal and non verbal sign in the emoticons that appear on Kaskus. The meaning of verbal sign and nonverbal sign in emoticon “marah” represents anger emotion. Emoticon “Ngakak” and “thumbup” represent enjoyable emotion. Emoticon “Sorry” and “Cool” represent sadness emotion. For future studies need to be conducted with an increased sample by using another media such as Whatsapp, YM, etc.
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Lahera, G., V. de los Ángeles, C. Fernández, M. Bardón, S. Herrera, and A. Fernández-Liria. "Sense of familiarity and face emotion recognition in schizophrenia." European Psychiatry 26, S2 (2011): 1427. http://dx.doi.org/10.1016/s0924-9338(11)73132-7.
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IntroductionPatients with schizophrenia show a deficit in emotion recognition through facial expression. Familiarity means the implicit memory of past affective experiences and it involves fast cognitive processes and it is triggered by certain signals.ObjectivesTo assess the emotion recognition in familiar and unfamiliar faces in a sample of schizophrenic patients and healthy controls.Methods18 outpatients diagnosed with schizophrenia (DSM-IVTR) and 18 healthy volunteers were assessed with the Ekman Test of emotion recognition in unfamiliar faces. In addition each subject was accompanied by 4 familiar people (parents, siblings or friends), which was photographed by expressing the 6 Ekman’s basic emotions.ResultsSchizophrenic patients recognize worse emotions in their relatives than in neutral faces, a greater extent than controls (Mann-Whitney U = 81, p = .01). The patient group showed a mean score on the Ekman test (neutral faces) lower than control group (16 (SD 2.38) versus 17.82 (2.13; U p = 0.03). Regarding familiar faces, the group patients showed a worse performance than the control group (13.22 (3.8) versus 17.18 (2.82); U p = 0.00). In both tests, the highest number of errors was with emotions of anger and fear. The patients group showed a lower level of familiarity and emotional valence to their families (U = 33, p < 0.01).ConclusionsThe sense of familiarity may be a factor involved in face emotion recognition and it may be disturbed in schizophrenia.
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Wierciński, Tomasz, Mateusz Rock, Robert Zwierzycki, Teresa Zawadzka, and Michał Zawadzki. "Emotion Recognition from Physiological Channels Using Graph Neural Network." Sensors 22, no. 8 (2022): 2980. http://dx.doi.org/10.3390/s22082980.
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In recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The key assumption of the validation was to analyze its correctness for the Circumplex model to further analyze the solution for emotion recognition in the Ekman modal. The novelty of this research is not only the utilization of a GNN network with GraphSleepNet architecture for emotion recognition, but also the analysis of the potential of emotion recognition based on differential entropy features in the Ekman model with a neutral state and a special focus on continuous emotion recognition during the performance of an activity The GNN was validated against the AMIGOS dataset. The research shows how the use of various modalities influences the correctness of the recognition of basic emotions and the neutral state. Moreover, the correctness of the recognition of basic emotions is validated for two configurations of the GNN. The results show numerous interesting observations for Ekman’s model while the accuracy of the Circumplex model is similar to the baseline methods.
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Zhang, Yong De, Shu Tong Li, Jin Gang Jiang, and Tian Hua He. "Research on Emotion Body Language Model of the Humanoid Robot." Applied Mechanics and Materials 494-495 (February 2014): 1278–81. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.1278.
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In order to improve the personification of human-robot emotion interaction, this paper based on the Euclidean space emotion model and Ekman theory of emotion, deduces the general formula of emotion characteristic value, establishes a improvement model of robot which can express the robots emotion through the body language. The general formula of emotional feature value make the models suitable for the expression of various emotions, and through body language to express the emotions, improves the emotion expression model generality and adaptability.
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Tak, Raghu. "A Quantifiable Analysis of Ambivalence in Tweets." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 691–99. http://dx.doi.org/10.22214/ijraset.2022.41340.
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Abstract: To detect emotions of the writer in any textual content is a requirement that has been persistent in the industry. Much of the research work has been done on this topic but only a handful of them explore the quantified association of the given text with the purpose of recognizing mixed emotions and emotional ambivalence, our work tends to do so. Emotional Ambivalence is a state in which person feels a blend of both positive and negative emotions. Therefore, we needed a suitable and brief emotion model capableof being bipolar to begin our work with, so we chose Paul Ekman’s Emotion model. This model focuses only on the six primary emotions which are: anger, fear, joy, sadness, surprise and disgust. In our work we used a Lexicon based approach for emotion recognition.The objective was achieved with the help of newly created lexicon for bi-grams that contained annotations according to their PMI scores. We also created a subset of Twitter Emotional Corpus (TEC) by passing it to our annotators, to test our approach. The automatic process through which the original corpus was created did have some wrong annotations; thereforea manual cross validation of this corpus was required. So, we chose three annotators for this purpose and fetched a uniform agreed corpus on whichwe worked further. The output of our approach detects a combination of the emotions felt associated with their respective values. Keywords: Emotion Analysis, Affect Computing, Sentiment Analysis
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Herrera, S., M. Bardón, C. Fernández, V. Ángeles, G. Lahera Forteza, and A. Fernández Liria. "Emotion facial expression in families of patients with schizophrenia." European Psychiatry 26, S2 (2011): 1399. http://dx.doi.org/10.1016/s0924-9338(11)73104-2.
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IntroductionPatients with schizophrenia show a deficit in emotion recognition through facial expression and the low sense of familiarity may be a factor involved. However, the emotion facial expression in families of patients could be disturbed and be another factor related to the deficit in emotion recognition and in sense of familiarity in schizophrenia.ObjectivesTo assess the emotion facial expression in a sample of 21 families of patients with schizophrenia and families of healthy controls.Methods22 healthy volunteers, all of them professionals of mental health, were assessed with the Ekman Test of emotion recognition in unfamiliar people which was photographed by expressing the 6 Ekman’s basic emotions. The task was composed of 42 pictures, half of them from families of patients and the other half from families of healthy control.ResultsVolunteers recognize worse emotions in relatives of patients than in relatives of control group and this difference was statistically significant (Wilcoxon W = -4.13; p = .001). The average of pictures correctly recognized from families of patients was lower than pictures from families of control group (54.28% vs. 82%).ConclusionsThe emotion facial expression in families of patients with schizophrenia seems worse than in families of healthy controls. It could be a factor involved in face emotion recognition deficit in schizophrenia.
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MOTORCA, MIHAELA CAMELIA, and MIHAELA GAVRILA ARDELEAN. "IMPROVING QUALITY OF LIFE THROUGH VIRTUAL REALITY: EMOTIONAL REGULATION IN ADULTS WITH INTELLECTUAL DISABILITIES USING THE LIMINAL VR PLATFORM." Journal Plus Education 37, no. 1 (2025): 458–69. https://doi.org/10.24250/jpe/1/2025/mcm/mga.
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This research paper aims to explore the integration of the virtual reality (VR) along with the emotional journaling in order to improve emotional regulation and also to reduce the selfharming behaviors in a participant with severe intellectual disabilities (American Psychiatric Association, 2013). The intervention included three sessions using the Cosmic Flow Scenario on the Liminal VR (ArborXR, n.d.) platform together with daily emotional journaling based on Paul Ekman’s universal emotions (Ekman, n.d.). The results highlighted major improvements in emotional self-regulation, reflected in an increased Emotional Balance Coefficient from 0.75 to 2.5 and the termination of self-harming behaviors. The observations underscore the potential of VR interventions in social work, emphasising their scalability for broader application, in spite of the challenges such as costs and accessibility. Future research is needed to investigate long-term impacts and group-based implementations (Yalon-Chamovitz & Weiss 2008).
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Vallverdú, Jordi. "Ekman’s Paradox and a Naturalistic Strategy to Escape From It." International Journal of Synthetic Emotions 4, no. 2 (2013): 1–7. http://dx.doi.org/10.4018/ijse.2013070101.
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The purposes of this paper are two: first of all, to show that blind-following of a oversimplistic model of emotions like happens with Ekman’s one is a bad situation for contemporary researchers from different disciplines. The author has called this situation, the Ekman’s paradox; at the same time, the complexity and divergence of ideas, concepts, methodologies and evidences among emotion researchers makes difficult to obtain the necessary agreement to facilitate future researches. Consequently, and this is the second purpose of this text is to define an unique and very specific emotion, pain, as a fulcrum from which to start to define a clear map of emotions. Pain has been chosen due to its specific and unique hardwired body mechanisms as well as a universal agreement among experts about its primordiality. Changing a word to make this explicit, one can have a new start point for the understanding of emotions: dolet, ergo sum.
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Abdulfatah Haron, Afnan, and Azharuddin Hashim. "Kajian Literatur Kesan Pengembangan Latihan Dalam Talian melalui Integrasi Teori Komunikasi Islam dan Teori Emosi Paul Ekman terhadap Latihan yang Berkesan." Journal of Management and Muamalah 13, no. 2 (2023): 41–59. http://dx.doi.org/10.53840/jmm.v13i2.167.
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Dalam era digital yang terus berkembang, aplikasi latihan dalam talian menjadi kaedah alternatif dalam meningkatkan keterampilan dan pengetahuan manusia. Walaupun kaedah ini menjadi terkenal kerana ia menawarkan peluang untuk mengikuti pelbagai jenis program latihan serta mempelajari ilmu tanpa batas geografi, perkara yang menjadi persoalan utama adalah tentang keberkesanan program latihan tersebut. Penelitian ini akan mengkaji adakah komunikasi yang berkesan akan memberikan impak terhadap keberkesanan program latihan tersebut. Kajian ini bertujuan untuk memberikan pandangan serta potensi dengan mengintegrasikan teori-teori Islam dan barat dalam keberkesanan program latihan. Dalam kajian ini, penyelidikan kualitatif digunakan dengan pengumpulan data melalui pembacaan penyelidikan lepas. Data dikumpul secara triangulasi bagi meningkatkan kesahan data. Hasil kajian mendapati bahawa integrasi kedua-dua teori ini mampu meningkatkan lagi keberkesanan program latihan terutama dalam aspek komunikasi di antara kedua-dua belah pihak semasa sesi latihan. Hasil kajian ini diharap dapat memberikan maklumat untuk mengenal pasti ekspresi emosi dan pemahaman tentang tindakbalas emosi dalam sesi latihan. Ianya juga diharap akan memberikan pemahaman yang lebih mendalam tentang penerapan Teori Komunikasi Islam dan Teori Emosi Paul Ekman semasa sesi latihan dalam talian. In the digital era, online training has gained popularity as an alternative to improve knowledge and skills. The ability to access knowledge from anywhere in the world is one of the main reasons why online training has become so popular. However, many people are still not sure how beneficial these online training really are. The purpose of this study is to determine if good communication affects the effectiveness of the training program. This study aims to shed light on how Islamic and Western theories, specifically Paul Ekman's theory of emotion and Islamic communication theory, could be integrated to increase the effectiveness of training programs. Using qualitative research methodology, data is collected by reviewing previous studies. To improve the veracity of the data, it is triangulated. The findings of the study suggest that the incorporation of both Paul Ekman’s theory of emotion with Islamic communication theory can further improve the effectiveness of the training program, especially in communication between instructors and trainees during the session. The findings of the study are expected to offer guidance for recognizing emotional displays and understanding emotional responses during training.
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Palmeri, Rosanna, Viviana Lo Buono, Lilla Bonanno, et al. "Impaired Recognition of Facial Emotion in Patients With Parkinson Disease Under Dopamine Therapy." Journal of Geriatric Psychiatry and Neurology 33, no. 5 (2019): 265–71. http://dx.doi.org/10.1177/0891988719882094.
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Introduction: Parkinson disease (PD) is a neurodegenerative disorder characterized by motor and nonmotor symptoms. The impaired ability to recognize facial emotion expressions represents an important nonmotor symptom. The aim of this study is to investigate the ability in recognizing facial emotion expressions in patients with PD under dopamine replacement therapy. Methods: Thirty medicated patients with PD and 15 healthy controls (HC) were enrolled. All participants performed the Ekman 60-Faces test for emotional recognition. All patients underwent a neuropsychological evaluation for global cognitive functioning, depression, and anxiety. Results: Patients with PD were impaired in recognizing emotions. Significant differences between PD and HC were found in Ekman 60-Faces test scores ( P < .001), and in Ekman 60-Faces test subscales, in particular, sadness, fear, disgust, anger, and surprise ( P < .001). Conclusions: The nigrostriatal dopaminergic depletion seems to determine emotional information processing dysfunction. This relevant nonmotor symptom could have consequences in daily living reducing interactions and social behavioral competence.
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Asma Sulaiman, Nor Anis, and Leelavathi Rajamanickam. "The State Art of Text Sentiment from Opinions to Emotion Mining." Journal of Engineering & Technological Advances 5, no. 2 (2020): 43–52. http://dx.doi.org/10.35934/segi.v5i2.43.
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This study is aiming to analyse the feelings expressed by the users in a text on a comment posted on social media. Text Mining and Emotion Mining can be analysed by using both technique of Natural Processing Language (NLP). Mostly on the previous study of text mining is using unsupervised technique and referring to Ekman’s Emotion Model (EEM) but it has restrained coverage of polarity shifters, negations and lack emoticon. In this study have proposed a Naïve Bayes algorithm as a tool to produce users’ emotion pattern. The most important contribution of this study is to visualize the emotion’s theory with the text sentiment based on the computational methods for classifying users’ feelings from natural language text. Then, the general system framework of extracting opinions to emotion mining has produced and capable use in any domains.
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Bluhm, Robyn. "Beyond the Basics: The Evolution and Development of Human Emotions." Canadian Journal of Philosophy Supplementary Volume 32 (2006): 73–94. http://dx.doi.org/10.1353/cjp.2007.0042.
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The suggestion that at least some emotions are modular captures a number of our intuitions about emotions: they are generally fast responses to a stimulus, they are involuntary, and they are easily distinguished (at least in most cases) from one another; we simply know that, for example, anger feels different than fear. Candidates for modular emotions are usually the so-called “basic” emotions - anger and fear are good examples of these. Defenders of emotion theories that focus on basic emotions, such as Paul Ekman in psychology and Paul Griffiths in philosophy, emphasize the advantages of theories that stress the evolutionary continuity of emotional expression and link emotions to the activity of neural circuits that are similar in human beings and other animals.In this paper, however, I will examine arguments for the discontinuity of emotions in human beings, as compared with other animals. Owing to a combination of cultural practices and neuroanatomy, both our emotional “wiring” and our emotions are unique.
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Liu, Yichen. "Brain-Computer Interface Application in Recognition and Regulation of Emotion." Theoretical and Natural Science 64, no. 1 (2024): 209–16. https://doi.org/10.54254/2753-8818/2024.17996.
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This paper investigates the application of Brain-Computer Interface (BCI) technology in the realms of emotion recognition and regulation. BCI technology facilitates direct communication between the brain and external devices, offering significant promise for improving human-environment interactions, particularly with regard to the identification and modulation of emotional states. By analyzing brain signals, such as electroencephalography, this study classifies emotions based on widely recognized models, including Ekmans model and the Russell circumplex model. To enhance the precision of emotion classification, machine learning algorithms, such as support vector machines and neural networks, are utilized. Moreover, this study explores BCIs potential in emotion regulation, focusing on neurofeedback and brain stimulation methods like transcranial direct current stimulation, which have shown therapeutic potential, particularly for disorders related to emotional dysregulation. Additionally, the paper delves into the integration of BCI with virtual reality to create immersive environments conducive to emotional therapy. Despite its considerable potential, BCI technology faces obstacles such as low data transmission rates and the complexities associated with user training. Nonetheless, the integration of BCI technology within Industry 4.0 frameworks holds promising opportunities for optimizing human-machine interactions and improving workplace safety.
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Todorovic, Zorana. "Evolutionary continuity between humans and non-human animals: Emotion and emotional expression." Theoria, Beograd 64, no. 4 (2021): 19–36. http://dx.doi.org/10.2298/theo2104019t.
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This paper deals with the evolutionary origin and the adaptive function of emotion. I discuss the view that emotions have evolved as functional adaptations in both humans and non-human animals in order to cope with adaptive challenges and to promote fitness. I argue that there is evolutionary continuity between humans and animals in emotions and emotional expressions, and discuss behavioural argument for this thesis, specifically, Darwin?s and Ekman?s research on similarities in how humans and animals express their basic emotions. In addition to this argument, I provide neuroscientific evidence that supports the claim that basic emotions are evolutionary old and shared among humans and many other animals. Finally, I conclude that animal emotions can be considered the bases and roots of our emotions that connect us to other sentient beings.
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Canan, MUTER SENGUL, and Deniz ERIS Engin. "An interpersonal Communication Aspect: The power of Moods in Interpreting Nonverbal Messages." International Journal of Management Sciences and Business Research 3, no. 3 (2014): 51–54. https://doi.org/10.5281/zenodo.3456800.
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The social perception and cognitive functions are two key factors in determining social behavior by evaluating social cues and the emotional responses of others. Emotions play a fundamental role in human cognition and researches on emotional communication mainly focus on facial expressions. Previous researches show agreement on a universal set of emotions which are associated with specific facial displays. Present research is conducted in line with discrete emotion theory postulating that “affect programs for basic emotions produce prototypical response configurations that include emotion-specific patterns of facial expressions” (Scherer, Ellgring, 2007:113) in order to interpret the interpersonal communication process which is the issue in every part of life especially in professional stage. The current study aims to examine the effect of moods on the perception of facial images in the scope of the Affect Program Theory of Facial Displays (APT) proposed by Ekman (1997). The process is interpreted from the categorical perspective of the perception of facial images. In order to determine the short-term mood of the participants, Positive and Negative Affect Schedule (PANAS) is administered and the facial expression images from the Pictures of Facial Affect (PFA) database (Ekman and Friesen, 2003) are used to measure the perception of facial images. The studied population of this preliminary study included 112 social sciences students. The results revealed a rather small negative effect of negative affectivity on affect perception throughtout facial pictures
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Hwang, SungHo, JiWon Hwang, and HyeonCheol Jeong. "Study on Associating Emotions in Verbal Reactions to Facial Expressions in Dementia." Healthcare 10, no. 6 (2022): 1022. http://dx.doi.org/10.3390/healthcare10061022.
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The purpose of this study was to provide basic data on cognitive therapy and to improve social support programs for the elderly with dementia by identifying the difficulties they experienced in emotional communication by identifying how they recognized emotions in verbal reactions to facial expressions using Ekman’s photographs of facial expressions and comparing their responses with the general elderly population. There were 141 participants in this study. Data collection was conducted from 3 April 2019 to 30 June 2019 in Seoul, in the Gyeonggi-do and Gangwon-do provinces of South Korea. This study performed descriptive research in which subjects made participative decisions with their guardian through recruitment. The tools used in this study included a general characteristic questionnaire and the Ekman 6 facial expressions photographs tool, which underwent intensive validity studies. The collected data were analyzed using the R version 3.5.1 statistic computing platform. The ability of the elderly with dementia to associate verbal expressions with facial expressions differed from that of the general elderly population. The rates of correct associations of verbal expressions to facial expressions were similar across dementia grades. There was a significant difference in the proportion of correct associations between positive and negative emotions in the elderly with dementia compared to the general elderly population. In the elderly with dementia, pictures showing fear, anger, and disgust had higher wrong rates of incorrect answers than correct answers. The average score of elderly with dementia in associating verbal expressions with six facial expressions was 2.69, which was even lower when they were asked to associate verbal expressions with pictures showing facial expressions of anger or disgust. This study shows that elderly persons with dementia have difficulties identifying two negative emotions (anger, disgust) and find it much easier to identify a positive emotion of happiness represented by a smiling face. Since the ability of the elderly with dementia to interpret verbal expressions to facial expressions was different from that of the general elderly population, careful attention and consideration are needed to support and communicate emotions to the elderly with dementia.
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Schiller, Devon. "The face and the faceness: Iconicity in the early faciasemiotics of Paul Ekman, 1957–1978." Sign Systems Studies 49, no. 3-4 (2021): 361–82. http://dx.doi.org/10.12697/sss.2021.49.3-4.06.
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Paul Ekman is an American psychologist who pioneered the study of facial behaviour. Bringing together disciplinary history, life study, and history of science, this paper focuses on Ekman’s early research during the twenty-year period between 1957 and 1978. I explicate the historical development of Ekman’s semiotic model of facial behaviour, tracing the thread of iconicity through his life and works: from the iconic coding of rapid signs; through the eventual turn from classifying modes of iconic signification using gestalt categories to classifying modes of producing iconic sign-functions using minimal units; to the role and importance of iconicity for the study of the facial expression of emotion, both in terms of the similarities between iconic and analogue signs as well as the differences between facial coding and linguistic signification. In this intellectual genealogy, I argue not only that Ekman relied extensively upon conceptualizations and terminologies from semiotic thought for the creation of the Facial Action Coding System (FACS), but also that the question of iconicity is the pivotal problem across the many discoveries and innovations in what I term ‘Ekmanian faciasemiotics’.
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Buluk, Katarzyna, and Celina Timoszyk-Tomczak. "„Co wyraża twarz?” – rozpoznawanie ekspresji emocjonalnej twarzy przez osoby głuche i słyszące." Psychologia Rozwojowa 25, no. 4 (2020): 101–10. http://dx.doi.org/10.4467/20843879pr.20.030.13438.
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„What does the Face Express?” – Recognition of Emotional Facial Expressions in Deaf and Hearing People An analysis of emotional functioning of deaf people is important for understanding their activities in different areas of life. Emotional functioning is related to emotional intelligence, which involves emotion perception and recognition as well as emotional expressiveness. The aim of the study was to compare the ability to recognize facial emotional expression among deaf and hearing people. The present study was conducted on 80 individuals (40 deaf people and 40 hearing people). The Emotional Intelligence Scale – Faces (Matczak, Piekarska, Studniarek, 2005) and a set of photographs used by Paul Ekman in his study of basic emotions were used for the data collection. The results obtained show that deaf people differ from hearing people in recognizing facial expressions. The analysis was conducted in terms of differences in recognition of expression of basic and complex emotions. The study included variables such as the moment of hearing loss (congenital or acquired deafness) or upbringing with deaf or hearing parents.
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Ayedoun, Emmanuel, and Masataka Tokumaru. "Towards Emotionally Expressive Virtual Human Agents to Foster L2 Production: Insights from a Preliminary Woz Experiment." Multimodal Technologies and Interaction 6, no. 9 (2022): 77. http://dx.doi.org/10.3390/mti6090077.
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In second-language communication, emotional feedbacks play a preponderant role in instilling positive emotions and thereby facilitating the production of the target language by second-language learners. In contrast, facial expressions help convey emotion, intent, and sometimes even desired actions more effectively. Additionally, according to the facial feedback hypothesis, a major component of several contemporary theories of emotion, facial expressions can regulate emotional behavior and experience. The aim of this study was to determine whether and to what extent emotional expressions reproduced by virtual agents could provide empathetic support to second-language learners during communication tasks. To do so, using the Facial Coding Action System, we implemented a prototype virtual agent that can display a collection of nonverbal feedbacks, including Ekman’ six basic universal emotions and gazing and nodding behaviors. Then, we designed a Wizard of Oz experiment in which second-language learners were assigned independent speaking tasks with a virtual agent. In this paper, we outline our proposed method and report on an initial experimental evaluation which validated the meaningfulness of our approach. Moreover, we present our next steps for improving the system and validating its usefulness through large-scale experiments.
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M. Usman Ashraf. "A Survey on Emotion Detection from Text in Social Media Platforms." Lahore Garrison University Research Journal of Computer Science and Information Technology 5, no. 2 (2021): 48–61. http://dx.doi.org/10.54692/lgurjcsit.2021.0502208.
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This paper provides an overview of the evolving field of emotion detection and identifies the current generation of methods of emotion detection from social media platforms as well as the challenges. The challenges in the field of current emotion detection are discussed in detail and potential alternatives are proposed to enhance the ability to detect emotions in real-life systems that emphasize interactions between humans and computers as well as advertisements, recommendation systems, and medical fields such as computer-based therapy. These solutions include the extraction of semantic analysis keywords, and ontology design with the evaluation of emotions. There are multiple models and classifications of emotions such as Ekman’s model (Happy, Anger, Sad, Disgust,Fear, Surprise), and Plutchik’s model (anger-fear, surprise-anticipation, joy-sadness, joy-sadness). Further, a systematic review of publications on textual emotions detection from social media platforms, state-of-the-art methods, and existing challenges presented. Finally, we conclude with some recommendations based on critical analysis of existing techniques and determine future research directions presented at last.
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Elías Chanchí Golondrino, Gabriel, Manuel Alejandro Ospina Alarcón, and Claudia Estella Hernandez Londoño. "Automated tool for conducting emotion analysis studies in perception surveys." Bulletin of Electrical Engineering and Informatics 14, no. 2 (2025): 1308–19. https://doi.org/10.11591/eei.v14i2.8238.
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Considering the growing need for companies to automate the analysis of customer opinions from different digital media, this paper outlines the development of an automated tool for emotion analysis in survey responses utilizing Ekman’s six-emotion model (joy, excitement, anger, sadness, fear, and boredom). The tool processes spreadsheets containing qualitative responses and generates the percentage distribution of emotions at both individual and aggregated levels. A case study conducted with 46 systems engineering students at the University of Cartagena during the COVID-19 pandemic showed that 'anger' was the most prevalent emotion (29.3%), followed by 'excitement' (19.4%), while 'boredom' was the least frequent (2.6%). The tool demonstrated an accuracy rate of 92% in classifying emotions, compared to 90% achieved through manual coding. These results highlight the tool’s effectiveness in automating emotion analysis, providing statistical and graphical reports that aid decision-making in academic and organizational contexts.
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Jain, Shikha, and Krishna Asawa. "EMIA: Emotion Model for Intelligent Agent." Journal of Intelligent Systems 24, no. 4 (2015): 449–65. http://dx.doi.org/10.1515/jisys-2014-0071.
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AbstractEmotions play a significant role in human cognitive processes such as attention, motivation, learning, memory, and decision making. Many researchers have worked in the field of incorporating emotions in a cognitive agent. However, each model has its own merits and demerits. Moreover, most studies on emotion focus on steady-state emotions than emotion switching. Thus, in this article, a domain-independent computational model of emotions for intelligent agent is proposed that have modules for emotion elicitation, emotion regulation, and emotion transition. The model is built on some well-known psychological theories such as appraisal theories of emotions, emotion regulation theory, and multistore human memory model. The design of the model is using the concept of fuzzy logic to handle uncertain and subjective information. The main focus is on primary emotions as suggested by Ekman; however, simultaneous elicitation of multiple emotions (called secondary emotion) is also supported by the model.
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Robinson, Lucy J., John M. Gray, Mike Burt, I. Nicol Ferrier, and Peter Gallagher. "Processing of Facial Emotion in Bipolar Depression and Euthymia." Journal of the International Neuropsychological Society 21, no. 9 (2015): 709–21. http://dx.doi.org/10.1017/s1355617715000909.
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AbstractPrevious studies of facial emotion processing in bipolar disorder (BD) have reported conflicting findings. In independently conducted studies, we investigate facial emotion labeling in euthymic and depressed BD patients using tasks with static and dynamically morphed images of different emotions displayed at different intensities. Study 1 included 38 euthymic BD patients and 28 controls. Participants completed two tasks: labeling of static images of basic facial emotions (anger, disgust, fear, happy, sad) shown at different expression intensities; the Eyes Test (Baron-Cohen, Wheelwright, Hill, Raste, & Plumb, 2001), which involves recognition of complex emotions using only the eye region of the face. Study 2 included 53 depressed BD patients and 47 controls. Participants completed two tasks: labeling of “dynamic” facial expressions of the same five basic emotions; the Emotional Hexagon test (Young, Perret, Calder, Sprengelmeyer, & Ekman, 2002). There were no significant group differences on any measures of emotion perception/labeling, compared to controls. A significant group by intensity interaction was observed in both emotion labeling tasks (euthymia and depression), although this effect did not survive the addition of measures of executive function/psychomotor speed as covariates. Only 2.6–15.8% of euthymic patients and 7.8–13.7% of depressed patients scored below the 10th percentile of the controls for total emotion recognition accuracy. There was no evidence of specific deficits in facial emotion labeling in euthymic or depressed BD patients. Methodological variations—including mood state, sample size, and the cognitive demands of the tasks—may contribute significantly to the variability in findings between studies. (JINS, 2015, 21, 709–721)
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Baia, Alina Elena, Giulio Biondi, Valentina Franzoni, Alfredo Milani, and Valentina Poggioni. "Lie to Me: Shield Your Emotions from Prying Software." Sensors 22, no. 3 (2022): 967. http://dx.doi.org/10.3390/s22030967.
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Deep learning approaches for facial Emotion Recognition (ER) obtain high accuracy on basic models, e.g., Ekman’s models, in the specific domain of facial emotional expressions. Thus, facial tracking of users’ emotions could be easily used against the right to privacy or for manipulative purposes. As recent studies have shown that deep learning models are susceptible to adversarial examples (images intentionally modified to fool a machine learning classifier) we propose to use them to preserve users’ privacy against ER. In this paper, we present a technique for generating Emotion Adversarial Attacks (EAAs). EAAs are performed applying well-known image filters inspired from Instagram, and a multi-objective evolutionary algorithm is used to determine the per-image best filters attacking combination. Experimental results on the well-known AffectNet dataset of facial expressions show that our approach successfully attacks emotion classifiers to protect user privacy. On the other hand, the quality of the images from the human perception point of view is maintained. Several experiments with different sequences of filters are run and show that the Attack Success Rate is very high, above 90% for every test.
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Barbieri, Giulia Francesca, Elena Real, Jessica Lopez, José Manuel García-Justicia, Encarnación Satorres, and Juan C. Meléndez. "Comparison of Emotion Recognition in Young People, Healthy Older Adults, and Patients with Mild Cognitive Impairment." International Journal of Environmental Research and Public Health 19, no. 19 (2022): 12757. http://dx.doi.org/10.3390/ijerph191912757.
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Background: The basic discrete emotions, namely, happiness, disgust, anger, fear, surprise, and sadness, are present across different cultures and societies. Facial emotion recognition is crucial in social interactions, but normal and pathological aging seem to affect this ability. The present research aims to identify the differences in the capacity for recognition of the six basic discrete emotions between young and older healthy controls (HOC) and mildly cognitively impaired patients (MCI). Method: The sample (N = 107) consisted of 47 young adults, 27 healthy older adults, and 33 MCI patients. Several neuropsychological scales were administered to assess the cognitive state of the participants, followed by the emotional labeling task on the Ekman 60 Faces test. Results: The MANOVA analysis was significant and revealed the presence of differences in the emotion recognition abilities of the groups. Compared to HOC, the MCI group obtained a significantly lower number of hits on fear, anger, disgust, sadness, and surprise. The happiness emotion recognition rate did not differ significantly among the three groups. Surprisingly, young people and HOC did not show significant differences. Conclusions: Our results demonstrated that MCI was associated with facial emotion recognition impairment, whereas normal aging did not seem to affect this ability.
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Kravljaca, Nikolina, Jennifer Stanley, and Eric Allard. "AGE DIFFERENCES IN EMOTION UTILITY KNOWLEDGE: COMPARING DISCRETE VERSUS DIMENSIONAL MODELS." Innovation in Aging 7, Supplement_1 (2023): 663. http://dx.doi.org/10.1093/geroni/igad104.2157.
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Abstract Do young and older adults have the same metacognitive schema for emotional utility? We examined young and older adults’ knowledge of which emotion would be best for achieving a goal (e.g., anger for confrontation). We captured responses using both a discrete emotions framework (e.g., happy; Ekman 1992) and a dimensional/circumplex model approach (e.g., arousal and valence; Russell, 1980) to determine which framework is most useful for understanding age differences in utilitarian emotion knowledge. Seventy-five young and 66 older adults indicated the most useful emotion when playing video games associated with different goals (Approach, Avoid, Confront, Analyze). Participants were asked to rate discrete emotions as well as identify the best combination of preferred valence and arousal on an affect grid. Two separate mixed-design ANOVAs were conducted for discrete emotion and dimensional ratings. Young and older adults exhibited similar preferences for both the discrete and circumplex model and chose the emotion with the most expected utility for each goal (e.g., happy for approach). One interesting age difference emerged where young adults endorsed the expected utilitarian emotion of sadness for the analyze goal to a greater extent than older adults. For the affect grid ratings, age differences were driven by arousal but not valence. We discuss how a discrete emotions approach may allow some clarity and a common language for interrogating the role of aging in utilitarian emotionality but may lack the nuance provided by the circumplex model.
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Dalkiran, M., E. Yuksek, and O. Karamustafalioglu. "Facial Emotion Recognition Ability in Psychiatrists, Psychologist and Psychological Counselors." European Psychiatry 41, S1 (2017): S157. http://dx.doi.org/10.1016/j.eurpsy.2017.01.2024.
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ObjectivesAlthough, emotional cues like facial emotion expressions seem to be important in social interaction, there is limited specific training about emotional cues for psychology professions.AimsHere, we aimed to evaluate psychologist’, psychological counselors’ and psychiatrists’ ability of facial emotion recognition and compare these groups.MethodsOne hundred and forty-one master degree students of clinical psychology and 105 psychiatrists who identified themselves as psychopharmacologists were asked to perform facial emotion recognition test after filling out socio-demographic questionnaire. The facial emotion recognition test was constructed by using a set of photographs (happy, sad, fearful, angry, surprised, disgusted, and neutral faces) from Ekman and Friesen's.ResultsPsychologists were significantly better in recognizing sad facial emotion than psychopharmacologists (6.23 ± 1.08 vs 5.80 ± 1.34 and P = 0.041). Psychological counselors were significantly better in recognizing sad facial emotion than psychopharmacologists (6.24 ± 1.01 vs 5.80 ± 1.34 and P = 0.054). Psychologists were significantly better in recognizing angry facial emotion than psychopharmacologists (6.54 ± 0.73 vs 6.08 ± 1.06 and P = 0.002). Psychological counselors were significantly better in recognizing angry facial emotion than psychopharmacologists (6.48 ± 0.73 vs 6.08 ± 1.06 and P = 0.14).ConclusionWe have revealed that the pyschologist and psychological counselors were more accurate in recognizing sad and angry facial emotions than psychopharmacologists. We considered that more accurate recognition of emotional cues may have important influences on patient doctor relationship. It would be valuable to investigate how these differences or training the ability of facial emotion recognition would affect the quality of patient–clinician interaction.
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Martin, Jeffrey J., Erin Snapp, Franziska Loetzner, Fatemeh Dehghan, Eva Prokešová, and Tania Bastos. "Culture and emotion in Paralympic swimming medalists." AUC KINANTHROPOLOGICA 58, no. 2 (2022): 103–14. http://dx.doi.org/10.14712/23366052.2022.7.
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The purpose of the present study was to examine if cultural identity was related to the emotional experiences of Paralympic (N = 83) swimmers’ upon winning medals at the 2016 Paralympic Games. Paralympic athletes’ countries (N = 5) were scored on Hofstede’s (2011) six cultural dimensions and athletes who won medals had their facial expressions analyzed to determine levels of basic emotions (i.e., happiness, sadness, anger, surprise, disgust, fear, and neutral) based on Ekman’s (1993) neuro-cultural theory of emotion. After controlling for medal won, and time and place expectation proxies, we found that happiness was negatively associated with long/short term orientation (r = –0.313, p < 0.004) and positively linked to indulgence/restraint (r = 0.210, p < 0.06). The emotion of neutral was positively associated with power distance (r = 0.239, p < 0.032) and long term/short term orientation (r = 0.290, p < 0.009) while being negatively linked to indulgence (r = –0.276, p < 0.013). Based on an abductive theory of the scientific method (Haig, 2005; 2008) we formed plausible theory-based explanations for our findings and concluded, given our study is the first of its nature, that researchers should continue this line of inquiry.
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Petrakova, A. V., E. I. Lebedeva, and E. N. Yurchik. "Recognition of Emotions in Relation to "Emotional Families"." Experimental Psychology (Russia) 17, no. 3 (2024): 4–15. http://dx.doi.org/10.17759/exppsy.2024170301.
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<p>The work is aimed at studying the performance of emotion recognition of people of different sex and age, expressed without specified criteria, in association with &laquo;emotional families&raquo;. The materials of an empirical online research obtained with the help of the crowdsourcing service &laquo;Yandex. Toloka&raquo;, in which 3,590 testers took part. The subjects guessed one of 14 emotions from the presented photographs (pride, anger, joy, irritation, fun, disgust, pleasure, sadness, relief, despair, interest, fear, surprise, anxiety). Photographs of five representatives of different age groups were presented: 7-9 years old (&laquo;junior school student&raquo;, 44 photos), 13-16 years old (&laquo;teenager&raquo;, 46 photos), 18-25 years old (&laquo;young woman&raquo;, 90 photos), 35 -50 years old (&laquo;woman&raquo;, 44 photos), 60 years and older (&laquo;older woman&raquo;, 70 photos). Subsequently, the experimenters compared the responses of the subjects with the criterion of matching the guessed emotion and its &laquo;emotional family&raquo; (according to P. Ekman). The main result is that the emotions were distributed by the subjects according to their orientation (valency) rather than according to the &ldquo;family&rdquo;. It remains debatable what could be the basis of such choices - the features of the stimulus material, or variability in the expression of emotions by models and their recognition by respondents.</p>
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Hidayah, Husni, Febriani Febriani, Khonsa Syahidah, et al. "Differences in Emotional Expressiveness Reviewed by Genderin TikTok Application Users." Journal of Social Science and Education Research 1, no. 6 (2024): 712–21. https://doi.org/10.59613/c492vn30.
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Students in early adulthood often face various emotional and social challenges. TikTok, a platform that allows users to share short video content, has become a popular medium for students to express their emotions. This study aims to examine differences in emotional expression between male and female students. Based on Ekman’s theory (2003), it is understood that several emotions are considered universal and are similarly recognized by individuals across different cultural backgrounds. These universal emotions include anger, disgust, fear, happiness, sadness, and surprise. This study hypothesizes that (1) there is a difference in emotional expression between males and females; (2) there is no difference in emotional expression between males and females. A quantitative approach with a survey design was used, employing a comparative research method. The sampling technique was purposive sampling, and data were collected through questionnaires distributed to students aged 17–24 years in Padang City. The participants included 15 male and 39 female students. Statistical analysis was performed using SPSS software. The results showed no significant difference in emotional expression between male and female TikTok users (p-value = 0.244 > 0.05). These findings are consistent with the research hypothesis.
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Csillag, Andrea. "Metaphors of Happiness in English and Russian." Romanian Journal of English Studies 13, no. 1 (2016): 91–98. http://dx.doi.org/10.1515/rjes-2016-0012.
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Abstract According to Ekman et al. (1972), happiness is one of the six universal basic human emotions. Kövecses (2000) claims that certain aspects of the conceptualization of emotions are universal or nearuniversal. The paper compares linguistic expressions to discuss the question of the universality of the emotion happiness and its metaphors in English and Russian.
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Hurley, Carolyn M., Wen Jing Teo, Janell Kwok, Tessa Seet, Erika Peralta, and Shuang Yu Chia. "Diversity from within: The Impact of Cultural Variables on Emotion Expressivity in Singapore." International Journal of Psychological Studies 8, no. 3 (2016): 50. http://dx.doi.org/10.5539/ijps.v8n3p50.
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<p>Culture is intrinsically linked with emotion expression, as culture provides rules regarding how to manage emotions when they occur. Thus far, existing literature has extensively compared norms for emotional expression and suppression, revealing significant differences among culturally distinct but also geographically distant groups (e.g., “collectivistic” Chinese versus “individualistic” U.S. Americans). The present study examines the impact of cultural diversity within Singapore, a heterogeneous Asian nation of 5.4 million residents. Using an expression suppression paradigm, eighty-three participants viewed emotion eliciting video clips and their expressions were analyzed according to the Emotion Facial Action Coding System (EmFACS, Ekman, Irwin, &amp; Rosenberg, 1994) for signs of happiness and disgust. Participants tasked to manage their expression were successful; however cultural indicators such as ethnicity, collectivism, and concern for face affected expressivity under both suppression and natural expression conditions. These results emphasize the importance of exploring culture within national boundaries, as multiple cultural factors (e.g., ethnic groupings, values, and face) influenced expression.</p>
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Saadi, Wafa, Fatima Zohra Laallam, Messaoud Mezati, Dikra Louiza Youmbai, and Nour Elhouda Messaoudi. "Enhancing emotion detection on Twitter: an ensemble clustering approach utilizing emojis and keywords across multilingual datasets." STUDIES IN ENGINEERING AND EXACT SCIENCES 5, no. 2 (2024): e10548. http://dx.doi.org/10.54021/seesv5n2-522.
Full textAbstract:
Social media has become a vital element of everyday life, shaping domains like business, politics, and personal interactions. Emotions play a critical role in these areas, necessitating accurate detection and interpretation, especially on platforms like Twitter (X), which feature short texts, various data formats (such as words, Emojis, and numbers), and multilingual content, including dialects. This study explores the importance of Emojis and keywords in positively interpreting emotions on Twitter (X). It uses ensemble-clustering techniques, combining different clustering algorithms like KMeans with various methods for a detailed analysis of emotional subtleties in social media discourse. By merging the semantic meanings of Emojis and keywords, a novel clustering ensemble algorithm is proposed to improve emotion detection accuracy. The approach is tested on two datasets: English and Arabic dataset, using the Ekman model, which classifies emotions into six basic categories (joy, sadness, anger, disgust, surprise, and fear). The findings from this integrated method show greater accuracy and precision compared to individual methods, providing valuable insights into public sentiments, enhancing customer satisfaction analysis, and improving social media monitoring tools.