Emotional Representations Research Articles

A Phenomenological Study of Representations of a Person with Down Syndrome in “Le huitième jour” by Jac van Dormael

The subject of the article is the world of a person with an intellectual disability in the comedy drama of Belgian director Jac von Dormael “Le huitième jour” (1996, “The Eighth Day”). The purpose of the article is phenomenological reading and analysis of the representation of a person with Down syndrome and his living world in the featured film, focusing on the emotional and social representation of the disability phenomenon. The approach of the filmmakers to the issue of disability is examined with the principles of social and film phenomenology, semantics and poetics of the artistic text. The research focuses on two perspectives of the phenomenon: a) the relationship of the main character Georges – a musical, theatrical, positive young man with Down syndrome – with his closest family and b) his dialogue with the wider society, which mainly emerges from the communication with Harry – the family father and a successful career teacher. The article makes analytical conclusions about emotional-social phenomena and their significance for the concept of disability, discussing other feature films of a similar period in the comparison. The research invites us to delve deeper into the representation of the experiences of joy and pain that is characteristic of the film “The Eighth Day” and at the same time provokes broader cultural associations.

El significado de los conceptos que aluden a emociones básicas en niños y adultos

Although basic emotions are considered universal, their representation, associations and meaning vary among cultures and social groups. Within the framework of the socio-constructivist theory, where the meanings develop in the social context, this paper analyzes and compares the semantic representations of six basic emotions (Joy, Sadness, Anger, Fear, Surprise and Disgust), evoked by 78 children between 9 and 11 years old and 78 adults between 20 and 40 years old. Participants had to list a series of properties/features for each concept in a Property Listing Task (PLT). With the lists produced by the participants, their frequencies and other statistical properties were calculated, and the matrix of distances between concepts was obtained from the vectors defined by each of them. Thus, using the six aforementioned emotions as stimuli, the semantic representation associated with each emotion was elaborated for each age range. Once these were obtained, an analysis was carried out to evaluate the intrinsic quality and the differences in: (1) quantity and types of features produced; (2) structure of each of the semantic networks obtained, both by means of quadratic assignment procedure (QAP) and hierarchical clustering algorithms; (3) network density (that describes the portion of the potential connections in a network that are actual connections) and entropy level (that describe the level of randomness and the amount of information encoded in a network); (4) comparative use of definition by negation; (5) qualitative analysis of the features associated with each emotional concept. To carry out the bulk of these activities and analysis, we used the tools and procedures provided by Social Network Analysis (SNA). As a result: (1) regarding the number of features, adults produced significantly more associations. A chi-square analysis found significant differences between groups in the type of features evoked, with a primacy of taxonomic for adults and introspective for children; (2) the quadratic assignment procedure found a significant level of association of .59 between the two age groups. The groupings performed at the lowest level of demand for linkage between cluster members distinguish positive emotions from negative ones; higher levels of demand begin to disaggregate the groupings: first fear and sadness are separated, then anger, then the dyad constituted by both versions of disgust. The emotion of greater commonality between children and adults is joy; (3) the density of the total network is higher in children than in adults, and the concepts of joy, disgust and sadness present a lower entropy in children than in adults; (4) Children produce considerably more definitions by the negative than adults; (5) the most similar emotion between both groups is joy and the most dissimilar is disgust. In children, disgust responds to gustatory stimuli, in adults it is used with social metaphorical value. The results obtained show the semantic representation of basic emotions in children and adults, finding both continuities (e. g. joy) and divergences (e. g. disgust) associated with the context and life experience. In both age groups, positive and negative emotions are found to be separated, which is consistent with theories on the importance of hedonic valence in the understanding of emotions. There are also differences in categorization, either more thematically or taxonomically oriented. https://doi.org/10.16888/interd.2022.39.3.11

Horses form cross-modal representations of adults and children.

Recently, research on domestic mammals' sociocognitive skills toward humans has been prolific, allowing us to better understand the human-animal relationship. For example, horses have been shown to distinguish human beings on the basis of photographs and voices and to have cross-modal mental representations of individual humans and human emotions. This leads to questions such as the extent to which horses can differentiate human attributes such as age. Here, we tested whether horses discriminate human adults from children. In a cross-modal paradigm, we presented 31 female horses with two simultaneous muted videos of a child and an adult saying the same neutral sentence, accompanied by the sound of an adult's or child's voice speaking the sentence. The horses looked significantly longer at the videos that were incongruent with the heard voice than at the congruent videos. We conclude that horses can match adults' and children's faces and voices cross-modally. Moreover, their heart rates increased during children's vocalizations but not during adults'. This suggests that in addition to having mental representations of adults and children, horses have a stronger emotional response to children's voices than adults' voices.

Emotion-Based Reinforcement Attention Network for Depression Detection on Social Media: Algorithm Development and Validation.

BackgroundDepression detection has recently received attention in the field of natural language processing. The task aims to detect users with depression based on their historical posts on social media. However, existing studies in this area use the entire historical posts of the users and select depression indicator posts. Moreover, these methods fail to effectively extract deep emotional semantic features or simply concatenate emotional representation. To solve this problem, we propose a model to extract deep emotional semantic features and select depression indicator posts based on the emotional states.ObjectiveThis study aims to develop an emotion-based reinforcement attention network for depression detection of users on social media.MethodsThe proposed model is composed of 2 components: the emotion extraction network, which is used to capture deep emotional semantic information, and the reinforcement learning (RL) attention network, which is used to select depression indicator posts based on the emotional states. Finally, we concatenated the output of these 2 parts and send them to the classification layer for depression detection.ResultsExperimental results of our model on the multimodal depression data set outperform the state-of-the-art baselines. Specifically, the proposed model achieved accuracy, precision, recall, and F1-score of 90.6%, 91.2%, 89.7%, and 90.4%, respectively.ConclusionsThe proposed model utilizes historical posts of users to effectively identify users’ depression tendencies. The experimental results show that the emotion extraction network and the RL selection layer based on emotional states can effectively improve the accuracy of detection. In addition, sentence-level attention layer can capture core posts.

ConGNN: Context-consistent cross-graph neural network for group emotion recognition in the wild

Group-level emotion recognition (GER) is challenging since it significantly relies on different individual facial expressions, complex group relationships, and contextual scene information. Due to complicated emotion interactions and emotion bias among multiple emotion cues, current techniques still fall short when it comes to detecting complex group emotion. In this study, we propose a context-consistent cross-graph neural network (ConGNN) for accurate GER in the wild. It can model multi-cue emotional relations and alleviate emotion bias among different cues, thus obtaining the robust and consistent group emotion representation. In ConGNN, we first extract the facial, local object, and global scene features to form multi-cue emotion features. Then, we develop a cross-graph neural network (C-GNN) for modeling inter- and intra-branch emotion relations, obtaining a comprehensive cross-branch emotion representation. To alleviate the effect of emotion bias during C-GNN training, we propose an emotion context-consistent learning mechanism with an emotion bias penalty to help obtain context-consistent group emotion, and then achieve robust GER. Furthermore, we create a new, more realistic benchmark, SiteGroEmo, and use it to evaluate ConGNN. Extensive experiments on two challenging GER datasets (GroupEmoW and SiteGroEmo) demonstrate that our ConGNN outperforms state-of-the-art techniques, with relative accuracy gains of 3.35% and 4.32%, respectively.

Lower emotional complexity as a prospective predictor of psychopathology in adolescents from the general population.

Emotional complexity (EC) involves the ability to distinguish between distinct emotions (differentiation) and the experience of a large range of emotions (diversity). Lower EC has been related to psychopathology in cross-sectional studies. This study aimed to investigate (a) whether EC prospectively predicts psychopathology and (b) whether this effect is contingent on stressful life events. To further explore EC, we compared the effects of differentiation and diversity. Adolescents from the general population (N = 401) rated 8 negatively valenced emotions 10 times a day for 6 consecutive days. Further, they completed the Symptom Checklist-90 (baseline and 1-year follow-up) and a questionnaire on past year's life events at follow-up. Logistic regression analyses tested whether EC-reflected by emotion differentiation (intraclass correlation coefficient [ICC]) and diversity (diversity index [DI])-predicted prognosis (good: remitting or lacking symptoms vs. bad: worsening or persisting symptoms). EC predicted prognoses but only when based on the ICC (OREC.ICC = 1.42, p = .02). An ECICC 1 SD above average increased the probability of good prognosis from .67 to .74. This effect was not related to stressful life events (OREC × Life events = 1.03, p = .86) and disappeared when emotion intensity (mean level) was taken into account (OREC = 1.20, p = .20). Predicting future prognosis does not necessitate complex measures of emotional experience (ICC, DI) but rather might be achieved through simpler indices (mean). The discrepant effects of the ICC and DI on prognosis suggest that impaired emotion representation (ICC) plays a more important role in vulnerability to mental ill health than does low diversity of emotions (DI). (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Acceptance and Adherence to COVID-19 Vaccination-The Role of Cognitive and Emotional Representations.

Vaccine hesitation is a topic of utmost importance, with the COVID-19 pandemic serving as a clear reminder of its timeliness. Besides evaluating COVID-19 vaccine acceptance in a sample of Portuguese people, this study aims at understanding cognitive and emotional representations related to vaccination, and their influence on vaccination hesitation. A cross-sectional online survey was conducted between 27 December 2020 and 27 January 2021. It assessed cognitive and emotional COVID-19 representations; vaccination status; cognitive and emotional representations of vaccination and perceived necessity and concerns about vaccines. Of 31 × 58 participants, 91% accepted taking a COVID-19 vaccine. Among several other significant findings, women (71.3%) more often considered that the pandemic affected their lives (p < 0.001) and were more often concerned with being infected (p < 0.001). Likewise, there were significantly more female participants concerned about taking a COVID-19 vaccine and its possible effects, when compared to the number of male participants (p < 0.001). The number of participants with a higher education level that were more worried about becoming infected was greater (p = 0.001), when compared with those less educated. Regarding age groups, people aged 18 to 24 had fewer concerned participants (9.6%), while the number of individuals aged 55 to 64 had the most (p < 0.001). Somewhat surprisingly, perceiving oneself as extremely informed about COVID-19 was not associated with greater vaccine acceptance (OR = 1.534 [1.160–2.029]; (p = 0.003)). Moreover, people aged 25 to 64 years old and with lower education level were more likely not to accept vaccination (OR = 2.799 [1.085–7.221]; (p = 0.033)). Finally, being more concerned about taking a vaccine lowers its acceptance (OR = 4.001 [2.518–6.356]; (p < 0.001)). Cognitive and emotional representations have a great impact and are reliable predictors of vaccine acceptance. Thus, it is of extreme importance that public health messages be adapted to the different characteristics of the population.

Illness perceptions in long-COVID: A cross-sectional analysis in adults

Symptoms may persist after an acute COVID-19 infection, a phenomenon termed long-COVID. Increasing attention is now directed toward these long-term effects, as many seem to be affected. So far, long-COVID was primarily discussed from a medical perspective, leaving psychological factors on health-related outcomes understudied. Thus, the present study contributes to the current literature by examining Leventhal’s common-sense model of self-regulation, investigating patients’ cognitive and emotional illness perceptions and their association with different health-related outcomes in the context of long-COVID. We examined 246 long-COVID patients (89.0% female, Mage = 45.29 ± 12.12 years), assessing illness perceptions, fatigue, depressive symptoms, anxiety, and quality of life in a cross-sectional survey study. Linear regression analyses were applied to model the unique effects of the illness perception dimension on health-related outcomes. More than half of the sample had elevated levels of depressive symptoms, anxiety, and fatigue. Illness perception dimensions explained between 28% and 37% of the variance across the analyzed health-related outcomes. More symptoms, higher perceived consequences, and higher emotional representation were related to worse health-related outcomes. In general, long-COVID was poorly understood (i.e., low coherence) and perceived as difficult to control (i.e., personal & treatment control). Health professionals involved in counseling should pay close attention to both cognitive and emotional illness perceptions to address possible ways of coping with long-COVID.

Social context effects on emotional language: The influence of the COVID-19 pandemic on the emotional evaluation of words

The COVID-19 pandemic has altered our routines, our conversations, the specific social contexts in which we hear or use certain words, and potentially, the representation of the words related to the disease and its consequences. Here we investigated whether the effects of the pandemic have changed the representation of the affective features of COVID-19-related words. To this aim, we collected new ratings of valence (from unpleasant to pleasant) and arousal (from calm to activated) dimensions for COVID-19-related words (e.g., hospital) and COVID-19-unrelated words (e.g., whale). Subsequently, we compared these scores with those from databases that reported ratings for the same pool of words before the pandemic. Our results showed significant changes in arousal for COVID-19-related words but not unrelated words, thus revealing that the pandemic social context modified their affective representation. These findings support the flexibility of emotional representations and the malleability and dynamicity of the mental lexicon as a function of contextual factors.

Different stages of emotional prosody processing in healthy ageing-evidence from behavioural responses, ERPs, tDCS, and tRNS.

Past research suggests that the ability to recognise the emotional intent of a speaker decreases as a function of age. Yet, few studies have looked at the underlying cause for this effect in a systematic way. This paper builds on the view that emotional prosody perception is a multi-stage process and explores which step of the recognition processing line is impaired in healthy ageing using time-sensitive event-related brain potentials (ERPs). Results suggest that early processes linked to salience detection as reflected in the P200 component and initial build-up of emotional representation as linked to a subsequent negative ERP component are largely unaffected in healthy ageing. The two groups show, however, emotional prosody recognition differences: older participants recognise emotional intentions of speakers less well than younger participants do. These findings were followed up by two neuro-stimulation studies specifically targeting the inferior frontal cortex to test if recognition improves during active stimulation relative to sham. Overall, results suggests that neither tDCS nor high-frequency tRNS stimulation at 2mA for 30 minutes facilitates emotional prosody recognition rates in healthy older adults.

Cognitive and emotional illness representation of people with chronic hepatitis B in Ghana: A qualitative inquiry.

Hepatitis B remains a public health concern in Ghana, with an estimated prevalence of 8.4% in adults and 14.3% in adolescents. This study explored the cognitive and emotional illness representations of persons with chronic hepatitis B who sought care at a tertiary hospital's liver clinic in Ghana. A qualitative exploratory descriptive design was adopted, and 15 participants were purposefully chosen for in-person interviews. The data was analyzed using the content analysis procedure. The findings revealed that participants' cognitive representations of hepatitis B infection varied. Some believed they got the infection through unsafe sexual practices, while others thought it was from their mother or spiritual sources. Participants' predominant emotional representations included shock, confusion, and fear. Education about the causes and management of hepatitis B should be addressed as part of patient care.

Emotion expression through spoken language in Huntington disease

Patients with Huntington's disease suffer from disturbances in the perception of emotions; they do not correctly read the body, vocal and facial expressions of others. With regard to the expression of emotions, it has been shown that they are impaired in expressing emotions through face but up until now, little research has been conducted about their ability to express emotions through spoken language.To better understand emotion production in both voice and language in Huntington's Disease (HD), we tested 115 individuals: 68 patients (HD), 22 participants carrying the mutant HD gene without any motor symptoms (pre-manifest HD), and 25 controls in a single-centre prospective observational follow-up study. Participants were recorded in interviews in which they were asked to recall sad, angry, happy, and neutral stories. Emotion expression through voice and language was investigated by comparing the identifiability of emotions expressed by controls, preHD and HD patients in these interviews. To assess separately vocal and linguistic expression of emotions in a blind design, we used machine learning models instead of a human jury performing a forced-choice recognition test. Results from this study showed that patients with HD had difficulty expressing emotions through both voice and language compared to preHD participants and controls, who behaved similarly and above chance. In addition, we did not find any differences in expression of emotions between preHD and healthy controls. We further validated our newly proposed methodology with a human jury on the speech produced by the controls. These results are consistent with the hypothesis that emotional deficits in HD are caused by impaired sensori-motor representations of emotions, in line with embodied cognition theories. This study also shows how machine learning models can be leveraged to assess emotion expression in a blind and reproducible way.

The Mathematical Analysis Model of Educational System in Music Courses in Colleges and Universities

Abstract This article first adopts a fuzzy mathematical analysis model and proposes a mathematical model of fuzzy characteristics of music categories. Second, the article extracts audio data characteristics and conducts music classification experiments. The article establishes a DNN-Bottleneck feature framework, extracts robust perceptual features from audio data, and then encodes to achieve fast audio perceptual hashing. Experiments verify the effect of different feature selections on the semantic space representation of music emotions and the impact on retrieval performance.

Analysis of Emotional Color Representation in Oil Painting Based on Deep Learning Model Evaluation

When an artist creates an oil painting, it is rich in emotion. Color is the main way to express emotion in oil painting. As far as the art field is concerned, color is an objective phenomenon that people can really feel its unique richness and brilliance, and different people will have different emotions when facing the same picture. Color itself is not emotional, but people have different psychological feelings by looking at different colors. This is the power of color. In the same way, color is also a carrier for painters to convey emotions in oil paintings. The study of emotional color expression in oil painting is more helpful for people to understand the emotion conveyed by oil painting. Color has an important role and an irreplaceable position in oil painting creation. In the creation of oil painting, color expression is combined with emotional expression. The creator conveys his experience and feelings in the form of color. In this paper, we look at the relationship between color and emotion, the emotional expression of color, and the expression of emotion in painting. The creators of oil paintings convey their feelings and experiences in the form of color, which plays a unique and important role in portraying the image of their works, expressing emotions, and creating an atmosphere, and we analyze and reveal how to use paint to express emotions in oil painting.

Emotional representation of music in multi-source data by the Internet of Things and deep learning

Emotional representation of music in multi-source data by the Internet of Things and deep learning

The Achievement Motive in the Brain: BOLD Responses to Pictures of Challenging Activities Predicted by Implicit Versus Explicit Achievement Motives.

The achievement motive refers to a preference for mastering challenges and competing with some standard of excellence. Along with affiliation and power motives, the achievement motive is typically considered to occur on the level of implicit versus explicit representations. Specifically, whereas implicit motives involve pictorial, emotional goal representations and facilitate corresponding action effortlessly, explicit motives involve propositional (“verbalized”) goal representations but need some effort to translate into action (McClelland et al., 1989). We used functional magnetic resonance imaging (fMRI) to investigate whether and to which degree the implicit and explicit achievement motives differentially predict blood-oxygen-level-dependent (BOLD) responses to pictures of individuals engaging in challenging activities. Whereas the implicit AM predicted activity in areas associated with emotion (orbitofrontal cortex) and visual processing (right dorsolateral prefrontal cortex, premotor and occipital cortices), the explicit AM predicted activity in areas associated with cognitive self-control or verbal goal processing (dorsal anterior cingulate cortex, left dorsolateral prefrontal cortex). The findings support the commonly assumed distinction between implicit and explicit motives with neuronal data. They also suggest that explicit motives require cognitive self-control to overcome potential lacks of motivation.

Knowledge Bridging for Empathetic Dialogue Generation

Lack of external knowledge makes empathetic dialogue systems difficult to perceive implicit emotions and learn emotional interactions from limited dialogue history. To address the above problems, we propose to leverage external knowledge, including commonsense knowledge and emotional lexical knowledge, to explicitly understand and express emotions in empathetic dialogue generation. We first enrich the dialogue history by jointly interacting with external knowledge and construct an emotional context graph. Then we learn emotional context representations from the knowledge-enriched emotional context graph and distill emotional signals, which are the prerequisites to predicate emotions expressed in responses. Finally, to generate the empathetic response, we propose an emotional cross-attention mechanism to learn the emotional dependencies from the emotional context graph. Extensive experiments conducted on a benchmark dataset verify the effectiveness of the proposed method. In addition, we find the performance of our method can be further improved by integrating with a pre-trained model that works orthogonally.

Lost in the Past: Emotions, History and International Relations

Lost in the Past: Emotions, History and International Relations

Region Dual Attention-Based Video Emotion Recognition.

To solve the emotional differences between different regions of the video frame and make use of the interrelationship between different regions, a region dual attention-based video emotion recognition method (RDAM) is proposed. RDAM takes as input video frame sequences and learns a discriminatory video emotion representation that can make full use of the emotional differences of different regions and the interrelationship between regions. Specifically, we construct two parallel attention modules: one is the regional location attention module, which generates a weight value for each feature region to identify the relative importance of different regions. Based on the weight, the emotion feature that can perceive the emotional sensitive region is generated. The other is the regional relationship attention module, which generates a region relation matrix that represents the interrelationship of different regions of a video frame. Based on the region relation matrix, the emotion feature that can perceive interrelationship between different regions is generated. The outputs of these two attention modules are fused to produce the emotional features of video frames. Then, the features of video frame sequences are fused by attention-based fusion network, and the final emotion feature of the video is produced. The experimental results on the video emotion recognition data sets show that the proposed method outperforms the other related works.

Would Illness Representations of COVID-19 and COVID-19 Fears During Clinic Visits Promote or Reduce Behavioral Intention to Seek Medical Consultations for Flu Symptoms? A Random Telephone Survey in Hong Kong, China.

BackgroundThe study investigated the level of behavioral intention to consult doctors for flu symptoms (BICDFS) during the Coronavirus Disease 2019 (COVID-19) pandemic and examined its associations with illness representations of COVID-19 and fear of COVID-19 during clinic visits in a general Chinese adult population.MethodsA random telephone survey was conducted among 300 residents in Hong Kong, China in April 2020 when the second wave of COVID-19 was just ended in the region. The participants were asked about their intention to consult doctors if they had mild or severe flu symptoms in the next week (from 1 = definitely no to 5 = definitely yes). Illness representations of COVID-19 were measured by the Chinese version of the Brief Illness Perception Questionnaire (BIPQ). The fear of COVID-19 during clinic visits were assessed by two single items. Linear regression adjusted for background variables and hierarchical strategies were employed.ResultsOf the participants, 52.3 and 92.0% showed an intention to consult doctors for mild and severe flu symptoms, respectively. Adjusted for background factors, COVID-19-related cognitive representations (consequences: standardized b = 0.15, p = 0.010; understanding: standardized b = 0.21, p = 0.001) and emotional representations (concern: standardized b = 0.17, p = 0.001; negative emotions: standardized b = 0.19, p = 0.001) were positively associated with BICDFS. In the hierarchical model, independent significant factors of BICDFS included understanding (standardized b = 0.16, p = 0.013) and negative emotions (standardized b = 0.17, p = 0.008). The fear-related variables showed non-significant associations with the BICDFS.ConclusionsPromotion of care-seeking behaviors for flu symptoms during the COVID-19 pandemic should consider improving people's understanding of COVID-19 and providing advice on related coping strategies for emotional responses to COVID-19.