Role Of Emotional Expression Research Articles

Cognitive reserve modulates mental health in adulthood

Cognitive Reserve (CR) reflects acquired knowledge, skills, and abilities throughout life, and it is known for modulating cognitive efficiency in healthy and clinical populations. CR, which was initially proposed to explain individual differences in the clinical presentation of dementia, has subsequently been extended to healthy ageing, showing its role in cognitive efficiency also during middle age. Recently, CR has been linked to affective processes in psychiatric conditions such as schizophrenia, major depressive and anxiety symptoms, and psychological distress, suggesting its potential role in emotional expression and regulation. Whether the role of CR in mental health extends to non-pathological adults, and whether this is only relevant in older age is not yet clear. The aim of this work was therefore to explore the relationship between CR and mental health in healthy adults, with a focus on middle adulthood (40–60). In a sample of 96 participants, we found a positive association between CR and mental health outcomes, such that a higher cognitive reserve index corresponded to fewer mental health reported symptoms. Specifically, a higher CR reflecting professional activities was associated with lower stress levels, especially in middle agers. Taken together, these data therefore suggest that engaging occupations may help maintain a robust mental health, especially by reducing stress symptoms during middle age. These results broaden previous findings suggesting that CR relates to affective components of mental health in middle aged and older adults.

Non-speech emotion recognition based on back propagation feed forward networks

Non-speech emotion recognition involves identifying emotions conveyed through non-verbal vocalizations such as laughter, crying, and other sound signals, which play a crucial role in emotional expression and transmission. This paper employs a nine-category discrete emotion model encompassing happy, sad, angry, peaceful, fearful, loving, hateful, brave, and neutral. A proprietary non-speech dataset comprising 2337 instances was utilized, with 384-dimensional feature vectors extracted. The traditional Backpropagation Neural Network (BPNN) algorithm achieved a recognition rate of 87.7% on the non-speech dataset. In contrast, the proposed Whale Optimization Algorithm - Backpropagation Neural Network (WOA-BPNN) algorithm, applied to a self-made non-speech dataset, demonstrated a remarkable accuracy of 98.6%. Notably, even without facial emotional cues, non-speech sounds effectively convey dynamic information, and the proposed algorithm excels in their recognition. The study underscores the importance of non-speech emotional signals in communication, especially with the continuous advancement of artificial intelligence technology. The abstract thus encapsulates the paper’s focus on leveraging AI algorithms for high-precision non-speech emotion recognition.

Determinants of social loneliness among older adults in job retirement and the role of emotional expressivity

Objectives The study examined the possibility that a mediating role of positive and negative emotional expressivity may contribute to understanding the associations between social loneliness and its previously identified predictors (i.e. health, age, sex, and social living situation). Method Self-reported assessments were collected from community-dwelling Swedish residents (aged 65 and above) in job retirement. Structural equation modeling with manifest variables was applied to cross-sectional data (N = 601) to analyze two competing models; one main-effect regression model, examining the predictive effect of emotional expressivity (along with health and sociodemographics) on social loneliness, and one mediation model, examining the mediating effect of emotional expressivity (using the bootstrapping technique provided in Mplus). Results The results indicated that the mediation model fit the data considerably better than the main-effect regression model (Δχ2 [Δdf = 8] = 72.69, p < 0.00001), and demonstrated a good fit on its own, with CFI = 0.986 and RMSEA = 0.030. This suggests that emotional expressivity contributes to the understanding of the connection between social loneliness and its previously identified predictors. Conclusion Recognizing the significance of emotional expressivity has the potential to enhance our understanding of loneliness in older adults, both in theory and in practice.

Depression Predicting Model For Social Media User’s Emotions Using Deep Learning Methods

There is a growing interest in leveraging social media platforms for the early identification of depression among the youth due to a rising occurrence. The study investigates the feasibility of utilizing Twitter data specifically emojis are included along with text content to predict degrees of depression among its users. The study examined Twitter data and used machine learning and deep learning to predict depression. Previous research on emotion detection mainly focused on text alone, but the contemporary landscape of communication integrates both text and emojis. The significant rise in usage of emojis in underlines their crucial role in emotional expression, necessitating their inclusion in analytical processes. The study shown the impact of combining text with emojis to determine the polarity of expressed sentiments. The study employed Convolutional Neural Networks (CNN) for sentiment analysis, with promising findings in reliably recognizing negative feelings and the potential for high performance to sentiment categorization. The study created a model capable of not only recognizing depression levels within a dataset but also identifying people who have higher-than-average levels of depression. This model acts as an early warning sign for mental health support, enabling mental health practitioners and social media platforms to offer timely assistance and interventions.

Dance and Social Interaction: Exploring the Role of Dance Art in Social Transformation

This article explores the significant role of dance art in social transformation, with a particular focus on its function in social interaction and communication. Initially, the article examines the historical perspective of how dance reflects and impacts social dynamics, analyzing the evolution of various dance styles and their societal influence. It then delves into dance as a medium of communication, highlighting its role in community building, cultural exchange, and cross-cultural understanding. The article pays special attention to the use of dance in social advocacy, exploring how dance raises public awareness about critical social issues. Furthermore, it investigates the psychological and sociological impacts of dance, including its role in emotional expression, identity formation, and group cohesion. The role of dance education in social development is also explored, emphasizing its value in fostering social skills and holistic development. Finally, the article discusses the challenges and opportunities faced by contemporary dance, as well as its potential in social innovation and technological integration. The article aims to underscore the enduring power of dance as a social art form and its unique position in driving social interaction and change.

Multi-modal speech emotion detection using optimised deep neural network classifier

ABSTRACT Speech emotion recognition (SER) has received significant attention recently and seems to be a critical aspect of human-computer interaction. The performance of the recent methods is not at the expected level there are many different strategies have been developed for SER. In the present situation, communication, non-verbal vocalisation, with a vocal sound plays an essential role in emotional expression. The multimodal database is considered for which the hybridised model of the audio-visual dependent emotion identification model is proposed. In this research, the optimised deep NN is used to recognise emotions from multimodal input data. For better performance in emotion recognition, the learner memorising optimisation fine-tunes the hyperparameters involved in the deep NN network classifier. The hybrid texture feature descriptor is proposed to improve classification outcomes from audio-video signals as well as accuracy. The learner memorising optimisation is used in the deep NN classifier to obtain the ideal parameters involved in exploring space with high accuracy. The metric values of the learner memorising optimisation-based deep NN have been evaluated using the Enter face’05 database and the proposed method obtained 97.490% accuracy, 98% sensitivity, and 97.490% specificity for the K-fold value 10% and 96.928%, 98.80%, and 96.928% for 90% training data.

3D Face Geometry Optimization Using Artificial Intelligence and Computer Graphics

Human face plays an indispensable role in emotional expression and information exchange, which attracts large number of researchers to study face recognition. Nowadays, with the rapid development of computer graphics, artificial intelligence, and other technologies, the ability of the human vision system to recognize facial expressions and facial organs is enhanced. More and more experts think about how to make the computer vision system have this capability. By combining artificial intelligence and computer graphics, this paper studies how to optimize the 3D face network model and extract geometric features for 3D face recognition. We propose a 3D face network model based on Poisson equation to realize face hole recognition and boundary preprocessing. Besides, we also establish the 3D face surface equation and equal face value extraction and enhance the face feature based on facial semantic information. We study the hole repair of 3D face model based on Poisson equation integrating semantic information and achieve the purpose of optimizing the 3D face model. After the optimization, the method is compared with mesh repair and Poisson repair, which demonstrates that our Poisson-based 3D face hole repairing model obtains the best results among compared methods.

HISTORY OF EMOTIONAL SUFFERING: FROM EMOTIONS TO NEEDS IN THE HISTORY OF EMOTIONS

ABSTRACTQuestions about the nature of emotions and the role of emotional expressions have been addressed frequently in the study of the history of emotions. However, the extent to which emotional suffering is present in the cultures and societies of the past is seldom queried. Our first goal is to identify criteria that historians of emotions can use to evaluate the emotional suffering of the people they study. We locate these criteria not in the theory of emotions, whether Norbert Elias's psychoanalytic theory or William M. Reddy's theory of emotives, but in the theory of basic, universal human needs proposed by Richard M. Ryan and Edward L. Deci. Although we agree with most contemporary historians of emotions that emotions themselves can be understood only within the context of a particular culture, we propose that additional inquiry into basic needs and their satisfaction could help historians of emotions cast more light on the inner lives of the members of the societies they investigate. Our second goal is to apply these insights to the case of acedia, a peculiar psychological state experienced by the Desert Fathers. We examine what acedia was for the Desert Fathers by analyzing Evagrius's writings. Our goal here is to capture what historians of emotions regularly do; that is, we aim to reconstruct how monks of the fourth century felt, expressed, and thought about emotions from within their own monastic culture. In addition, we analyze acedia from the perspective of the theory of needs. In this way, we hope to show how the theory of needs can help historians in their endeavors to understand the past.

A Translation Analysis of Nursery Rhymes in the English Version of The Straw House Based on Relevance Theory: a Cognitive Approach

The Straw House (草房子) written by Cao Wenxuan (曹文轩) had encountered overseas coldness before the writer won the Hans Christian Andersen Award in 2016. Such a phenomenon has been attributed to three main reasons: copyright agents, translation challenges, promotion and review of social media. Taking the translation of five nursery rhymes as the research object which play a vital role in the English version of The Straw House , this study analyzed and explored the translation approaches of those nursery rhymes adopted by Sylvia Yu, Julian Chen and Christopher Malone. Through case analysis, a concrete analysis was made of the translation methods of the nursery rhymes, contrasted with the Chinese Mother Goose Rhymes by Isaac Taylor Headland, a book of similar genre. Based on Relevance Theory, a discussion of advantages and disadvantages of the translations was made before solutions were put forward to the translation problems which led to the failure to communicate the author’s intention to the target readers. It was found out that despite the attention to the reproduction of the original content by using literal strategy, the translation ignored the individual characteristics, contextual functions and the role in emotional expression that nursery rhymes play. In this process, the separation of the original information intention and communication intention, the loss of contextual presupposition and implication all resulted in the absence of relevancy which fails the communication. Based on the identified translation problems, some solutions were proposed. It is hoped that these solutions will bring inspirations to the translation of nursery rhymes in children’s literature.

Comment: Moving (Further) Beyond Private Experience: On the Radicalization of the Social Approach to Emotions and the Emancipation of Verbal Emotional Expressions

Emotions have traditionally been viewed as intrapersonal phenomena. Over the past decades, theory and research have shifted toward a more social perspective that emphasizes the role of emotional expressions in coordinating social interaction. I provide a brief history of this ongoing paradigm shift, which reveals two critical developments. The first concerns a continuing shift in emphasis on the social-communicative rather than individual-level functions and effects of emotions—the radicalization of the social approach to emotion. The second concerns a growing awareness that emotions can be expressed through multiple modalities, including words—the emancipation of verbal emotional expressions. I discuss theoretical challenges and opportunities presented by these developments and consider their implications for understanding emotions as a source of social influence.

Surgical Method of a Corner Mouth Lift.

Background:The mouth and perioral area play a primary role in emotional expression, and these are among the most important areas projecting youth and attractiveness. A downturned corner of the mouth presents negative feelings such as sadness, depression, and tiredness. A corner mouth lift (CML) may restore more attractive and youthful appearance, which can favorably affect first impression, self-esteem, and the quality of life in patients.Methods:From December 2016 to September 2018, 498 patients underwent a CML. There were 434 women and 64 men. The mean age was 38.99 years (19–63 years) and 34.19 years (21–67 years) in female and male patients, respectively. A total of 432 cases (86.7%) were primary surgical cases, whereas 66 (13.3%) were secondary cases. There were 178 patients (35.7%) who only underwent CML, whereas the remaining patients (64.3%) underwent the CML contemporarily with other perioral surgery such as subnasal lift.Results:Most patients were satisfied with the results. However, some patients showed unsatisfactory outcomes such as hypertrophic scar, asymmetry, persistent swelling, or undercorrection. The most common complaints immediately after surgery were swelling and bruise, which were improved spontaneously within 1–2 weeks. Postoperative scar and undercorrection were the most common complications that required revision surgery.Conclusions:CML showed reliable and satisfactory outcomes in most patients. It could be a good option for patients who desire CML regardless of their age.

The Customer Isn’t Always Right: The Implications of Illegitimate Complaints

Due to the common business practice of the “customer is always right,” many companies have a risk of dealing with illegitimate complaints. Although illegitimate complaints are a major issue in the hospitality industry, no study has yet examined the impact of illegitimate customer complaining behavior on customers who can witness the complaining and recovery process of others. To fill this gap, this research examines the effects of service recovery aimed at illegitimate customers on customers who witness the complaints’ behavioral reactions (revisit intention, tipping behavior, intention to complain) and the role of emotional expression. A 2 (Service recovery aimed at other customer; good vs. poor) × 2 (Legitimacy of complaining behavior of other customers: legitimate vs. illegitimate) × 2 (Emotional expression: aggressive vs. calm) scenario-based between-subjects factorial experiment is utilized. This research provides evidence that witnessing illegitimate complaints of other customers and the subsequent service recovery aimed at those complainers impacts the behavioral reactions of customers who witness that situation. This study broadens the service recovery literature by incorporating third-party justice theory with illegitimate customer behavior by specifically examining the unique case where the firm is not responsible for the service recovery. In addition, the findings address the benefit to service firms by understanding the impact of witnessing other customers’ service recovery treatment on observers’ subsequent behavioral intentions.

Cingulum bundle abnormalities and risk for schizophrenia

BackgroundThe cingulum bundle (CB) is a major white matter fiber tract of the limbic system that underlies cingulate cortex, passing longitudinally over the corpus callosum. The connectivity of this white matter fiber tract plays a major role in emotional expression, attention, motivation, and working memory, all of which are affected in schizophrenia. Myelin related CB abnormalities have also been implicated in schizophrenia. The purpose of this study is to determine whether or not CB abnormalities are evident in individuals at clinical high risk (CHR) for psychosis, and whether or not cognitive deficits in the domains subserved by CB are related to its structural abnormalities. MethodsDiffusion Tensor Imaging (DTI) was performed on a 3 T magnet. DT tractography was used to evaluate CB in 20 individuals meeting CHR criteria (13 males/7 females) and 23 healthy controls (12 males/11 females) group matched on age, gender, parental socioeconomic status, education, and handedness. Fractional anisotropy (FA), a measure of white matter coherence and integrity, radial diffusivity (RD), thought to reflect myelin integrity, trace, a possible marker of atrophy, and axial diffusivity (AD), thought to reflect axonal integrity, were averaged over the entire tract and used to investigate CB abnormalities in individuals at CHR for psychosis compared with healthy controls. ResultsSignificant group differences were found between individuals at CHR for psychosis and controls for FA (p = 0.028), RD (p = 0.03) and trace (p = 0.031), but not for AD (p = 0.09). We did not find any significant correlations between DTI measures and clinical symptoms. ConclusionThese findings suggest abnormalities (possibly myelin related) in the CB in individuals at CHR for psychosis.

The Role of Emotional Expression and Eccentricity on Gaze Perception.

The perception of another’s gaze direction and facial expression complements verbal communication and modulates how we interact with other people. However, our perception of these two cues is not always accurate, even when we are looking directly at the person. In addition, in many cases social communication occurs within groups of people where we can’t always look directly at every person in the group. Here, we sought to examine how the presence of other people influences our perception of a target face. We asked participants to judge the direction of gaze of the target face as either looking to their left, to their right or directly at them, when the face was viewed on its own or viewed within a group of other identity faces. The target face either had an angry or a neutral expression and was viewed directly (foveal experiment), or within peripheral vision (peripheral experiment). When the target was viewed within a group, the flanking faces also had either neutral or angry expressions and their gaze was in one of five different directions (from averted leftwards to averted rightwards in steps of 10°). When the target face was viewed foveally there was no effect of target emotion on participants’ judgments of its gaze direction. There was also no effect of the presence of flankers (regardless of expression) on the perception of the target gaze. When the target face was viewed peripherally, participants judged its direction of gaze to be direct over a wider range of gaze deviations than when viewed foveally, and more so for angry faces than neutral faces. We also find that flankers (regardless of emotional expression) did not influence performance. This suggests that observers judge that angry faces were looking at them over a broad range of gaze deviations in the periphery only, possibly resulting from increased uncertainty about the stimulus.

The Role of Emotional Expression in Accessing Social Networks: The Case of Newcomers' Blogs

The Role of Emotional Expression in Accessing Social Networks: The Case of Newcomers' Blogs

Prominence features: Effective emotional features for speech emotion recognition

Emotion-related feature extraction is a challenging task in speech emotion recognition. Due to the lack of discriminative acoustic features, classical approaches based on traditional acoustic features could not provide satisfactory performances. This research proposes a novel type of feature related to prominence, which, together with traditional acoustic features, are used to classify seven typical different emotional states. To this end, the author group produces a Chinese Dual-mode Emotional Speech Database (CDESD), which contains additional prominence and paralinguistic annotation information. Then, a consistency assessment algorithm is presented to validate the reliability of the annotation information of this database. The results show that the annotation consistency on prominence reaches more than 60% on average. Subsequently, this research analyzes the correlation of the prominence features with emotional states using a curve fitting method. Prominence is found to be closely related to emotion states, to retain emotional information at the word level to the greatest possible extent and to play an important role in emotional expression. Finally, the proposed prominence features are validated on CDESD through speaker-dependent and speaker-independent experiments with four commonly used classifiers. The results show that the average recognition rate achieved using the combined features is improved by 6% in speaker-dependent experiments and by 6.2% in speaker-independent experiments compared with that achieved using only acoustic features.

#Stupidcancer: Exploring a Typology of Social Support and the Role of Emotional Expression in a Social Media Community

ABSTRACTSocial network sites (SNSs) like Twitter continue to attract users, many of whom turn to these spaces for social support for serious illnesses like cancer. Building on literature that explored the functionality of online spaces for health-related social support, we propose a typology that situates this type of support in an SNS-based open cancer community based on the type (informational or emotional) and the direction (expression or reception) of support. A content analysis applied the typology to a 2-year span of Twitter messages using the popular hashtag “#stupidcancer.” Given that emotions form the basis for much of human communication and behavior, including aspects of social support, this content analysis also examined the relationship between emotional expression and online social support in tweets about cancer. Furthermore, this study looked at the various ways in which Twitter allows for message sharing across a user’s entire network (not just among the cancer community). This work thus begins to lay the conceptual and empirical groundwork for future research testing the effects of various types of social support in open, interactive online cancer communities.

Prediction errors to emotional expressions: the roles of the amygdala in social referencing

Social referencing paradigms in humans and observational learning paradigms in animals suggest that emotional expressions are important for communicating valence. It has been proposed that these expressions initiate stimulus-reinforcement learning. Relatively little is known about the role of emotional expressions in reinforcement learning, particularly in the context of social referencing. In this study, we examined object valence learning in the context of a social referencing paradigm. Participants viewed objects and faces that turned toward the objects and displayed a fearful, happy or neutral reaction to them, while judging the gender of these faces. Notably, amygdala activation was larger when the expressions following an object were less expected. Moreover, when asked, participants were both more likely to want to approach, and showed stronger amygdala responses to, objects associated with happy relative to objects associated with fearful expressions. This suggests that the amygdala plays two roles in social referencing: (i) initiating learning regarding the valence of an object as a function of prediction errors to expressions displayed toward this object and (ii) orchestrating an emotional response to the object when value judgments are being made regarding this object.

Emotional dysregulation and anxiety control in the psychopathological mechanism underlying drive for thinness.

Emotional dysregulation is a process which consists in mitigating, intensifying, or maintaining a given emotion and is the trigger for some psychological disorders. Research has shown that an anxiety control plays an important role in emotional expression and regulation and, in addition, for anorexia nervosa (AN) and, more in general, in drive for thinness. Scientific literature suggests that in AN there is a core of emotional dysregulation and anxiety control. The aim of this study is to explore the roles of emotional dysregulation and anxiety control as independent or third variables in a mediational regression model related to drive for thinness. One hundred fifty-four clinical individuals with anorexia participated in the study and all completed a set of self-report questionnaires: eating disorders inventory version 3 (EDI-3), DERS, and the anxiety control questionnaire. The data confirmed a mediational model in which the relation between emotional dysregulation and drive for thinness is mediated by anxiety control. The current study partially supports a clinical model in which emotional dysregulation is a distal factor in eating disorders while the mediator variable anxiety control is a proximal factor in the psychopathological process underlying it.

From the Heart: The Role of Emotional Expression in the Legitimation of Ontario Wine

Extant institutional research and the primarily cognitive frameworks upon which it is based do not explicitly consider the role emotional expression plays in legitimation processes. In this study, ...