Understanding Of Emotions Research Articles

From Categorical to Dimensional: A Multifaceted Approach to Emotions

Current emotion research utilizes two primary frameworks: categorical and dimensional. Each framework offers unique insight, but also faces challenges in capturing the full spectrum of emotional experience. This study compares and integrates categorical and dimensional approaches to better understand their applications and limitations in emotion research, particularly in enhancing human-centered designs. Using Plutchik’s Wheel and the Self-Assessment Manikin (SAM), 238 participants rated their emotional responses to AI- generated images of various driving scenarios. Subsequently, the categories of emotions were mapped into the valence and arousal space. The integration of categorical and dimensional models revealed significant variability in individual interpretations of different emotions, highlighting the complexity and non-uniformity of emotional experience. These findings suggest that emotions may require more than two dimensions for full representation. A multifaceted approach that combines both frameworks can offer a comprehensive understanding of emotions and is essential for developing effective, empathetic, human-centered applications.

The emotion regulation antecedents of tertiary EFL instructors and their use of reappraisal and suppression

This study aims to contribute to the understanding of teachers' emotions in terms of their antecedents and ER strategies (cognitive reappraisal and expressive suppression). To provide an in-depth understanding, a case study was conducted with eight tertiary instructors. The study utilized a narrative frame, semi-structured interviews, and vignettes. The results revealed the emotion-triggering antecedents were related to interactions with students, non-teaching responsibilities, and interactions with colleagues. The participants responded to these emotions using various expressive suppression (e.g., hiding an emotion's impact) and reappraisal strategies (e.g., adjusting expectations). The findings emphasized the situational and dynamic nature of ER.

Enhancing Parental Understanding of Emotions in Children with Developmental Language Disorder: An Online Parent-Led Intervention Program.

Many children with developmental language disorder (DLD) have emotion recognition and regulation difficulties, but there are currently no known interventions enhancing emotional awareness in this population. This study explores the impact of parents' perspectives regarding children with DLD emotional understanding through a parent-led online emotion recognition (ER) intervention. Ten parents of children with DLD aged 6-11 participated in the study. A nonconcurrent multiple baseline design was employed, allowing for a rigorous analysis of changes in parental beliefs over time. Weekly data were collected through the Parents' Beliefs About Children's Emotions Questionnaire. Interviews were also conducted to gain deeper insights into parents' perceptions regarding the ER skills of their children. Results indicated that parents' beliefs about the need for guiding and supporting their child's ER skills increased over the intervention. Interviews also supported this, and three main themes were generated. The intervention program increased parents' awareness of (a) the importance of ER for children with DLD, (b) emotion-focused communication and engagement with their child, and (c) the integration of emotions into daily life. This study is the first known study that explores parents' beliefs about children with DLD ER skills, highlighting the importance of supporting parents through accessible interventions.

Promoting theory of mind and emotion understanding in preschool settings: an exploratory training study.

This new exploratory study is part of a larger ongoing follow-up project. Its specific aim was to verify whether an innovative European Program, primarily designed to enhance children's social and emotional learning, led to gains in theory of mind and emotion understanding when implemented in preschool settings. Thirty-four children (mean age: 56.4 months; SD: 10.1; range: 40-70 months) participated in the study. They were randomly and equally divided into a training group and a control group. The training sample completed eight linguistic-conversational activities drawn from the Program, in groups of 5 to 6 children, over 8 weeks. The activities were based on listening to stories and/or watching videos and then thinking and talking about the inner world (thoughts and emotions) of the story characters as well as the participants' own inner states. During the training phase, the children in the control group engaged in drawing or free play activities. At both the pre-test and post-test phases of the study, all the children completed a language test, a battery of theory of mind (ToM) tasks (including 'change of location' and 'unexpected content' tasks), and the Test of Emotion Comprehension which evaluates nine components of emotion understanding (EU). The validated national versions of the tests were administered in all cases. Significant differences were identified between the training and control groups. Indeed, the participants in the Program training activities, which were based on conversational exchanges between an adult and a group of children, as well as among the children themselves, outperformed the control participants on both overall theory of mind and overall emotion understanding. A more detailed analysis showed that the training group outperformed the control group in relation to both specific components of EU and the 'change of location' ToM task. The results of this exploratory study suggest that the Program is effective at enhancing preschoolers' social understanding and thus merits implementation in preschool settings.

A Neurocognitive Approach Reveals Paul’s Embodied Emotional Strategies

Joy is a central theme in Philippians. Joy is also a central emotional habit Paul deploys and encourages as a strategy for building community. In this paper, the examination of Philippians through recent developments in the neurocognitive study of emotions first illuminates how Paul cultivates emotional habits, like joy. Second, a neurocognitive approach to understanding emotions can explain how repeatedly choosing joy functions to alleviate suffering by restoring balance in the nervous system. Finally, shared emotional habits with the Philippian community, like shared somatic practices, build sustaining connections among the members. Intentional deployment of emotional practices, as Paul demonstrates and encourages in the Philippians, is a strategy for building the body of Christ. Such a neurocognitive understanding of emotional habits and bodily practices among community members in the Christ body points to a corporate experience of shared healing and neurocognitive resilience. Might we consider this somatic embodiment of shared emotions, what Paul calls “the same mind that is in Christ Jesus”, also a participation in Christ’s soteria (healing/salvation)?

Interpersonal interactions, sense of loneliness and perceived depressive emotions among older adults: A cultural-psychological perspective from heterogeneous roles of different relationships

In the context of the “Chinese Differential Mode of Association” in traditional Chinese culture, this paper examines the heterogeneous effects of interpersonal interactions in different relationships on older adults’ depressive emotions from a cultural-psychological perspective. Results using data from Chinese General Social Survey demonstrate that: interactions with children are the most helpful in reducing perceived depression for the elderly, followed by communications with siblings and relatives. However, interactions with friends and other fellows do not significantly reduce older people’s perceived depression. This reflects the “Chinese Differential Mode of Association” in interpersonal relationships. When using different perceived depression measures, and Double Debiased Machine Learning (DDML) approaches for robustness and endogeneity tests, above findings are very robust. The impact mechanism is that interactions with children and siblings reduce depressive emotions by decreasing older adults’ sense of loneliness, while communications with others do not have such a significant effect. This paper further discusses the roles of different types of interactions with adult children. It is found that receiving and providing emotional support can prominently decrease depressive emotions for older people, whereas the effects of monetary support and non-material assistance are less pronounced. In addition, interpersonal interactions’ impacts are more significant for those who are female, older than 75 and with poorer health, as well as older people who exercise less frequently, have higher social status, and hold more traditional beliefs. In the current context of active promotion of healthy aging, findings of this paper have important implications for a deeper understanding and scientific management of depressive emotions among the elderly.

Deep learning approaches for recognizing facial emotions on autistic patients

Autistic people need continuous assistance in order to improve their quality of life, and chatbots are one of the technologies that can provide this today. Chatbots can help with this task by providing assistance while accompanying the autist. The chatbot we plan to develop gives to autistic people an immediate personalized recommendation by determining the autist’s state, intervene with him and build a profil of the individual that will assist medical professionals in getting to know their patients better so they can provide an individualized care. We attempted to identify the emotion from the image's face in order to gain an understanding of emotions. Deep learning methods like Convolutional neural networks and Vision Transformers could be compared using the FER2013. After optimization, CNN achieved 74% accuracy, whereas the VIT achieved 69%. Given that there is not a massive dataset of autistic individuals accessible, we combined a dataset of photos of autistic people from two distinct sources and used the CNN model to identify the relevant emotion. Our accuracy rate for identifying emotions on the face is 65%. The model still has some identification limitations, such as misinterpreting some emotions, particularly "neutral," "surprised," and "angry," because these emotions and facial traits are poorly expressed by autistic people, and because the model is trained with imbalanced emotion categories.

The Relationship Between AI and Unemployment Rate and the Solution

Technological advancements and significant strides in artificial intelligence have undeniably propelled economic growth. Integrating AI into production processes enhances productivity and efficiency. AI systems can operate continuously without breaks, and advanced technologies minimize the risk of human errors, producing high-quality goods and reducing costs. Ever since the inception of ChatGPT, the discourse surrounding the potential replacement of human labor by artificial intelligence has been a recurring theme. However, specific industries within the job market are resistant to being replaced by artificial intelligence, as they require distinct human qualities like creativity, emotion, and decision-making skills. These professions require problem-solving, interpersonal skills, emotional understanding, moral decision-making, and various unique human talents. This paper analyses the relationship between AI and the unemployment rate and the solution. It revealed the temporary decline in production efficiency, including short-term production efficiency reduction and long-term productivity improvements. Various policies can be implemented to address the issues mentioned, including initiatives to enhance education and improve the transparency of AI applications.

College Students With Intellectual and Developmental Disabilities' Experiences, Conception, and Development of Emotional Wellness.

This study aimed to understand the ways in which college students with intellectual and developmental disabilities (IDD) experience and develop their understanding of emotions and emotional wellness. Semi-structured interviews with college students with IDD were conducted. The research team utilized consensual qualitative research (CQR) to analyze interviews and came to consensus in generating domains, core ideas, and a cross-analysis to answer the research question, "What are the experiences of college students with IDD in developing an understanding of emotions and emotional wellness?" Findings suggest college students with IDD have experience developing and maintaining their emotional wellness, though they may experience barriers prior to and during college enrollment. Limitations and implications for future research are discussed.

Multimodal Affective Communication Analysis: Fusing Speech Emotion and Text Sentiment Using Machine Learning

Affective communication, encompassing verbal and non-verbal cues, is crucial for understanding human interactions. This study introduces a novel framework for enhancing emotional understanding by fusing speech emotion recognition (SER) and sentiment analysis (SA). We leverage diverse features and both classical and deep learning models, including Gaussian naive Bayes (GNB), support vector machines (SVMs), random forests (RFs), multilayer perceptron (MLP), and a 1D convolutional neural network (1D-CNN), to accurately discern and categorize emotions in speech. We further extract text sentiment from speech-to-text conversion, analyzing it using pre-trained models like bidirectional encoder representations from transformers (BERT), generative pre-trained transformer 2 (GPT-2), and logistic regression (LR). To improve individual model performance for both SER and SA, we employ an extended dynamic Bayesian mixture model (DBMM) ensemble classifier. Our most significant contribution is the development of a novel two-layered DBMM (2L-DBMM) for multimodal fusion. This model effectively integrates speech emotion and text sentiment, enabling the classification of more nuanced, second-level emotional states. Evaluating our framework on the EmoUERJ (Portuguese) and ESD (English) datasets, the extended DBMM achieves accuracy rates of 96% and 98% for SER, 85% and 95% for SA, and 96% and 98% for combined emotion classification using the 2L-DBMM, respectively. Our findings demonstrate the superior performance of the extended DBMM for individual modalities compared to individual classifiers and the 2L-DBMM for merging different modalities, highlighting the value of ensemble methods and multimodal fusion in affective communication analysis. The results underscore the potential of our approach in enhancing emotional understanding with broad applications in fields like mental health assessment, human–robot interaction, and cross-cultural communication.

The Affective Dimensions of Historical Empathy: Opportunities, Problems, and Challenges

Emotions and feelings play an important role within history education. Yet, the affective dimensions (feelings, emotions, connections) of learning about the past are understudied within research on historical empathy—defined here as a cognitive-affective process of attempting to understand the thoughts, feelings, experiences, decisions, and actions of people from the past within their historical contexts. Drawing from interviews with secondary school history teachers in Canada, this article offers insight into teachers’ perspectives on constructive ways that they approach the affective dimensions within history classrooms, as well as problems and challenges that arise when they intentionally elicit emotions or encounter them unexpectedly. In doing so, the article aims to further conceptualize the affective dimensions of historical empathy and expand understandings of emotions in history and social studies education, while positioning these discussions in relation to history education in Canada.

Revisiting the Heider and Simmel experiment for social meaning attribution in virtual reality

In their seminal experiment in 1944, Heider and Simmel revealed that humans have a pronounced tendency to impose narrative meaning even in the presence of simple animations of geometric shapes. Despite the shapes having no discernible features or emotions, participants attributed strong social context, meaningful interactions, and even emotions to them. This experiment, run on traditional 2D displays has since had a significant impact on fields ranging from psychology to narrative storytelling. Virtual Reality (VR), on the other hand, offers a significantly new viewing paradigm, a fundamentally different type of experience with the potential to enhance presence, engagement and immersion. In this work, we explore and analyze to what extent the findings of the original experiment by Heider and Simmel carry over into a VR setting. We replicate such experiment in both traditional 2D displays and with a head mounted display (HMD) in VR, and use both subjective (questionnaire-based) and objective (eye-tracking) metrics to record the observers’ visual behavior. We perform a thorough analysis of this data, and propose novel metrics for assessing the observers’ visual behavior. Our questionnaire-based results suggest that participants who viewed the animation through a VR headset developed stronger emotional connections with the geometric shapes than those who viewed it on a traditional 2D screen. Additionally, the analysis of our eye-tracking data indicates that participants who watched the animation in VR exhibited fewer shifts in gaze, suggesting greater engagement with the action. However, we did not find evidence of differences in how subjects perceived the roles of the shapes, with both groups interpreting the animation’s plot at the same level of accuracy. Our findings may have important implications for future psychological research using VR, especially regarding our understanding of social cognition and emotions.

The Impact of ChatGPT-like Artificial Intelligence on Ideological and Political Education

The rapid development of artificial intelligence technology and application led by ChatGPT has brought a strong impact on all walks of life, and has also brought application possibilities for the ideological and political education work in colleges at the forefront of the Internet to build an "intelligent core". ChatGPT can provide information and knowledge, promote interaction and exchange, assist teaching and research, and provide more comprehensive and diversified support and services for the ideological and political education. However, due to its lack of emotional understanding ability, lack of experience and intuition of human teachers, its application will be accompanied by some risks. In this context, this paper studies the opportunities and challenges of the application of ChatGPT in the network ideological and political education in colleges and universities, in order to improve the quality of the ideological and political education in colleges.

Down-modulation of functional ventral striatum activation for emotional face stimuli in patients with insula damage.

Insula damage results in substantial impairments in facial emotion recognition. In particular, left hemispheric damage appears to be associated with poorer recognition of aversively rated facial expressions. Functional imaging can provide information on differences in the processing of these stimuli in patients with insula lesions when compared to healthy matched controls (HCs). We therefore investigated 17 patients with insula lesions in the chronic stage following stroke and 13 HCs using a passive-viewing task with pictures of facial expressions testing the blood oxygenation dependent (BOLD) effect in predefined regions of interest (ROIs). We expected a decrease in functional activation in an area modulating emotional response (left ventral striatum) but not in the facial recognition areas in the left inferior fusiform gyrus. Quantification of BOLD-response in ROIs but also voxel-based statistics confirmed this hypothesis. The voxel-based analysis demonstrated that the decrease in BOLD in the left ventral striatum was driven by left hemispheric damaged patients (n = 10). In our patient group, insula activation was strongly associated with the intensity rating of facial expressions. In conclusion, the combination of performance testing and functional imaging in patients following circumscribed brain damage is a challenging method for understanding emotion processing in the human brain.

Sentient libraries: empowering user expeditions with emotional artificial intelligence

Purpose The study aims to forecast emotional artificial intelligence’s (EAI) trajectory in libraries, provide actionable implementation recommendations and outline potential research paths. It seeks to establish ethical benchmarks, considering emotional well-being alongside informational needs. Understanding EAI in libraries becomes pivotal, envisioning libraries as empathetic, user-centric spaces. Design/methodology/approach This research uses a multifaceted approach, intertwining comprehensive literature analysis, illustrative case studies and forward-thinking assessments. It combines foundational knowledge from various academic sources, integrating real-world examples of EAI implementations in library settings. The methodology goes beyond observational analysis, scrutinizing ethical quandaries and societal impacts. It comprehensively explains EAI’s role while delineating guidelines for responsible integration and future exploration. Findings Integrating emotional intelligence (EI) enhances resource curation, fosters inclusive virtual learning environments and elevates continuous service enhancement in libraries. It allows tailored recommendations, emotionally perceptive virtual assistants and adaptive responses to diverse emotional needs, reshaping libraries into empathetic spaces. Research limitations/implications Ethical considerations pose significant challenges, especially regarding privacy, security and fair usage of EAI. Libraries must mitigate biases and ensure equitable emotional services. Adapting to diverse emotional needs within library services requires a delicate balance between empathetic approaches and upholding ethical standards. Practical implications EAI revolutionizes user experiences, offering personalized, engaging interactions while ensuring ethical, inclusive library environments. Implementing EAI requires navigating biases and ethical complexities, demanding continuous refinement and using user-focused strategies. Social implications Integrating EAI redefines the library’s role, transforming libraries into emotionally perceptive hubs catering to users’ intellectual and emotional needs. It emphasizes fairness, trust and ethical conduct in providing empathetic, inclusive services. Originality/value This research pioneers the integration of EI in libraries, offering insights into ethical frameworks, bias mitigation and user-centric approaches. It envisions libraries as empathetic, responsive spaces, enriching lives through emotional understanding and responsiveness.

Preschoolers’ moral judgment and punishment attribution: Longitudinal links to theory of mind and emotion understanding

AbstractUnderstanding what others think and feel, an essential ingredient of social functioning, develops early on, allowing children to understand and evaluate other people's actions. To assess whether those actions break or uphold moral rules (moral judgments), children must consider the agent's intentions and whether the action harms or helps others. The present study investigated longitudinally the changes and interrelations between cognitive and affective perspective‐taking and moral evaluations in 3‐ to 5‐year‐old preschoolers (N = 92, 43 girls). We assessed children's first‐order theory of mind and their ability to understand other people's emotions. Next, we presented them with two moral stories which measured how children evaluated the “good” or “bad” nature of the character's intention, and whether the character deserved to be punished. Controlling for inhibitory control—which is thought to help individuals integrate information about intention—and for time across development, our main findings showed that moral judgment was positively associated with theory of mind and that both moral judgment and punishment were positively associated with the ability to understand other people's emotions. There were developmental effects for each of the measured variables, improvements being visible 15 months later, especially in the case of the theory of mind and punishment attributions. We discuss our findings in light of recent models of moral judgment regarding the processes involved in children's moral judgments and put forward future methodological directions.

Application of Artificial Intelligence Methods in Processing of Emotions, Decisions, and Opinions

The rapid advancement of artificial intelligence (AI) and natural language processing (NLP) has profoundly impacted our understanding of emotions, decision-making, and opinions, particularly within the context of the Internet and social media [...]

Relationship between emotion comprehension, vocabulary, and verbal working memory in intellectual developmental disorders: involvement of verbal reasoning skills

ABSTRACT This study investigated the role of language-related abilities in emotion comprehension among young people with non-specific intellectual developmental disorders (NS-IDDs). Forty children and adolescents with NS-IDDs completed tasks assessing emotion comprehension, receptive vocabulary, verbal reasoning skills, and verbal working memory. Results showed that emotion comprehension was better predicted by comprehension of abstract words and verbal working memory, and that these two predictors were themselves predicted by verbal reasoning skills. These results therefore suggest a link between emotion understanding and verbal reasoning, which could be mediated by abstract vocabulary and verbal working memory. These findings provide insight into the relationships between emotion comprehension and language-related abilities in NS-IDDs.

LINGUISTIC FEATURES OF THE CONCEPT OF “LOVE” IN RUSSIAN AND ARABIC CONTEXTS

The concept of love is a multifaceted and polysemous concept that has been studied in various disciplines, including philosophy, psychology, linguistics, sociology and neuroscience. In a philosophical context, love is analyzed from the point of view of its emotional, ethical, existential, anthropological and metaphysical aspects. The emotional aspect of love encompasses feelings of affection, passion and tenderness, while the ethical aspect views love as a virtue and the basis of moral behavior. The existential aspect emphasizes the role of love in the search for meaning in life and self-realization, and the anthropological aspect explores its significance for the development of personality and human nature. In the context of globalization, the concept of love is also influenced by global processes, transforming family structures and intimate relationships in different cultures. Thus, the concept of love is a central and polysemantic element of human experience, enriching our understanding of emotions, relationships and cultural norms. The article demonstrates that love, despite its universal nature, acquires unique features and meanings depending on the cultural context in which it manifests itself. The article demonstrates that love, despite its universal nature, acquires unique features and meanings depending on the cultural context in which it manifests itself. The article examines various aspects of love and its manifestations in the context of various cultural traditions. The author analyzes how cultural norms, values, and historical conditions influence the perception and expression of love in different societies.

Are all emotions social? Embracing a pluralistic understanding of social emotions

While the importance of social emotions is widely recognized, the question whether all emotions are social and what this would mean for the category ‘social emotions’ is yet to be addressed systematically. Emotion theorists and researchers so far have proposed different candidates for social emotions. These include non-basic emotions, self-conscious emotions, higher-cognitive emotions, and defining social emotions via their social functions. This paper looks at these different candidates for social emotions and briefly discusses their issues. Discussing the candidates and their issues motivates embracing a pluralistic approach to social emotions. In a further step, the paper will look at approaches exploring how social factors impact emotions in general. This serves as a basis for explaining what it would mean to propose that all emotions are social. After reviewing different candidates for social emotions and looking at the impact of social factors on emotions in general, the paper will propose that a pluralistic understanding of social emotions is needed to embrace the different ways in which social emotions may function. Embracing a pluralistic understanding of social emotions does not mean, however, that all emotions are social emotions.