Emotional Knowledge Research Articles

Knowledge and Attitudes Regarding Geriatric Depression: A Descriptive Study Among Adult Saudi Citizens.

Depression is a leading cause of disability and contributes significantly to the overall burden of any disease. In Saudi Arabia, the geriatric population over 65 is continuing to expand and will contribute to a significant portion of the Saudi community. As the population of the elderly continues to grow as a result of longer lifespans, there will be an increase in the number of individuals in this population suffering from undiagnosed geriatric depression. This study aims to assess the general population's attitude and knowledge about the symptoms, signs, and complications of geriatric depressiontoimprove the quality of life of the elderly. This is a cross-sectional study, using a convenience sample of 2,320 participants, between March to September 2022. However, due to age, nationality, and incomplete responses that did not meet our inclusion criteria, 629 participants were excluded, and the sample size narrowed to 1,691. A structured questionnaire was designed to collect data based on a comprehensive literature review. An online survey was distributed to Saudi citizens. The participants were between 18 and 50, both women and men and only Saudi nationals were included. This age group was selected as a convenient, purposeful sample, assuming that this portion of the population will be able to be enrolled in an electronic survey in addition to their direct contact with elderlies as possible caregivers. All analyses were performed using IBM SPSS Statistics software for Windows, version 26.0 (IBM Corp., Armonk, NY). The data were analyzed using a nonparametric test because they were not normally distributed. The study comprised 1,691 participants from diverse regions of Saudi Arabia, with a significant gender disparity observed, including 1,249 females (73.9%) and 442 males (26.1%). The majority of our participants were between 18-29 years, accounting for 55.2% of the sample. Descriptive statistics revealed prevalent beliefs among participants regarding geriatric depression. Notably, 35.1% strongly agreed and 19.3% agreed that depression affects individuals of particular ages, while a significant portion (47.1%) disagreed with the statement that depression in the elderly is a health problem. Additionally, 33.9% disagreed that geriatric depression can lead to suicide, and 33.8% believed it can be prevented. Analysis of actions and behaviors highlighted avoidance tendencies, with only 1.5% of the population strongly agreeing to treat a family member with geriatric depression and a majority (63.7%) avoiding interaction due to fear of harm, including 29.5% who strongly agreed and 34.2% who agreed. Gender differences were evident in emotional responses and knowledge levels, with females exhibiting higher emotional responses (mean score 15.63±2.92) and males displaying greater knowledge (mean score 14.90±3.36). In this study, we investigated the knowledge and attitudes of Saudis toward depression in the elderly. Findings revealed an inadequate understanding of geriatric depression, with many not recognizing it as a health condition and underestimating its severity. Negative emotions and behaviors, such as shame and reluctance to provide support, were prevalent. Gender, education level, and region influenced attitudes and knowledge. These results underscore the need for targeted interventions to raise awareness and challenge the stigma surrounding geriatric depression in Saudi Arabia.

Schadenfreude in Working Women of Lahore: A Phenomenological Study

Human beings have been gifted with a diverse and wonderful set of emotions. They have the ability to not only experience their own feelings, but also empathize with the emotions of others, such as being happy for someone who has conceived. Unfortunately, humans are not always moral or kind. Some people truly take pleasure in others' misery, as opposed to feeling compassion for them. Schadenfreude is defined as a feeling of satisfaction, pleasure or happiness brought on by witnessing another person's sorrow or misfortune. The present study aimed to explore the lived experiences and coping strategies of schadenfreude in working women. The sample consisted of six female faculty members which were recruited through purposive sampling. Phenomenological research design was used in this study. Semi-structured interviews were conducted with six faculty members. The data was analyzed using interpretative phenomenological analysis (IPA). Two sets of themes emerged from data analysis. First set of themes was related to the lived experiences of schadenfreude. The superordinate themes included social factors, personality traits, biology and upbringing, psychological indicators and organizational influences. The other set of themes was regarding the coping strategies employed by faculty to overcome schadenfreude. The superordinate themes consisted of short-te­­rm and long-term coping strategies. The findings have long-term implications it will advance our knowledge of negative emotions and the effects of interpersonal conflict on job satisfaction, stress levels, and workers' general wellbeing and therefore help to promote teamwork and long-term prosperity for the organization.

Psychological Principles in Education: Reviewing William James' Impact on Teaching Practices

The well-known psychologist William James made significant contributions to educational theory that significantly affected how teachers imparted knowledge. William James was a prominent psychologist in the late 19th and early 20th century who made substantial contributions to education. Theory and practice in education have been greatly influenced by his knowledge of human consciousness, emotion, and behavior. This review of the literature aims to find out how James' psychological theories have influenced contemporary teaching methods. This review attempts to provide educators with useful guidance for enhancing student growth and learning, with an emphasis on James' theories and their relevance to modern classrooms. The significance of the study is to know about James’ psychological theories that influence modern teaching pedagogies and learning and by studying this study educators can find guidance for improving and enhancing student learning and growth. The conclusion of the study shows that modern teaching methods are highly influenced by James’ ideas like habit formation, students’ attention and engagement, and the nature of awareness moreover, implementation of James’ ideas may help teachers improve the students’ results and performance as these provide more interesting, engaging, and effective learning environments. James’ philosophies are useful for the implication of modern educational trends like active learning techniques, the creation of mindful activities, social and emotional learning, and student-centered learning.

허난설헌의 내방가사에 드러난 중국적 감성지식의 수용 방식

Heo Nanseolheon(許蘭雪軒) was a female writer in the middle of Joseon(朝鮮) Dynasty and created a number of works in which her true heart was put. Most of Heo Nanseolheon’domestic lyric are based on Chinese literary forms. This is the result of the benefits she received from his prestigious family in his youth. For this reason, it is natural that the accumulated knowledge of Nanseolheon became the foundation of his creation. Based on his accumulated creative awareness, Nanseolheon boldly used the Shiti(詩題) and Cipai(詞牌) in addition to freely using the form of Chinese literature itself. However, this is not a mere borrowing, but a complete understanding and understanding of China’s emotions. Therefore, Nanseolheon is trying to perfectly match his works with Chinese emotional knowledge. Not only that, but also in the framework of Chinese emotional knowledge that he formed, the artist’s affection melts without hesitation. Thus, the domestic lyric of Heo Nanseolheon are resurrected and revived in China after his death. And the background is that his has genuinely released his own story with the device of Chinese emotional knowledge. The distribution in China was also influenced by the background in which the artist’s voice, Heo Nanseolheon, was introduced to the familiar form and sensibility and was able to accept to accept it without any objection. Therefore, the purpose of this study is to examine the Chinese emotional knowledge and its acceptance method revealed in Heo Nanseolheon’domestic lyric. The attempt of this study has the value of examining the traces of aerodynamics that have been processed into more improved ones by accepting Chinese things.

Emotion Knowledge Relates to Cortisol for Children Attending Head Start Preschool

ABSTRACT Research Findings: The ability to manage emotions is thought to be important for regulating stress at a physiological level, yet no prior published studies have examined young children’s emotion understanding or knowledge in relation to the stress hormone cortisol. The present study investigated the statistical relation between emotion knowledge (EK) and cortisol levels for 307 young children ages 3–5 years who attended Head Start preschool, and their primary caregivers. All of the child participants faced economic hardship and 80% were Black, Indigenous, and People of Color (BIPOC) and thereby positioned to experience systemic racism. At the start of the preschool year, EK, or understanding of emotions, was assessed using a well-validated emotion matching task and basal cortisol levels were measured via salivary assay. Results of a multiple linear regression analysis revealed that, after accounting for demographic covariates, greater EK was associated with lower cortisol. Practice or Policy: The finding that EK relates to cortisol levels in early childhood highlights the importance of addressing emotional competence in early intervention programs. Notably, the relationship may be bidirectional and reducing stress levels also may facilitate advancing young children’s emotion understanding. Interventions that promote EK and reduce stress levels may advance overall school readiness.

The electronic knowledge publishing based on intellect modeling

This paper focuses on a new concept based on modeling human intelligence for electronic knowledge publishing. It discusses the limitations of current publishing methods in solving real-life problems and proposes the need for a new type of publishing. It identifies two main streams of publishing: Emotional publishing and knowledge texts publishing, highlighting the challenges of the latter. The article evaluates various attempts in the field of Artificial Intelligence, such as expert systems and neural networks, in terms of knowledge transfer and problem-solving. It suggests that understanding the principles of human intelligence, as exemplified by the character Sherlock Holmes, can contribute to the development of the proposed “Intellect Modeling” concept. Overall, the article presents a comprehensive proposal that addresses the shortcomings of existing publishing models and offers a new approach that incorporates advancements in Artificial Intelligence and Knowledge Management.

Proprioception, Emotion and Social Responsiveness in Children with Developmental Disorders: An Exploratory Study in Autism Spectrum Disorder, Cerebral Palsy and Different Neurodevelopmental Situations.

Proprioception has long been linked with emotional dysregulation in neurotypical adults. Neuropediatric disorders such as autism spectrum disorder (ASD) and cerebral palsy (CP) are distinct entities and yet both present with deficits and challenges in sensory processing and the regulation of emotions. This study aimed to explore the relationship between proprioception and emotional-social performance in children and to compare proprioception and emotional-social performance in different underlying neurodevelopmental conditions. For this purpose, this cross-sectional study included 42 children with ASD, 34 children with CP and 50 typically developing peers. Proprioceptive acuity, proprioceptive reactive behavior as well as emotion regulation and social responsiveness were assessed. The results show a significant correlation between proprioceptive deficits and emotional difficulties in this pediatric sample, with distinct proprioceptive impairment patterns according to the underlying neurological disorder. Children with CP showed significant emotional knowledge deficits, while children with ASD predominantly showed challenges in social responsiveness. These data thus suggest a differentiated impact of proprioception on emotional-social performance in neurodevelopmental disorders and highlight proprioception as a potential therapeutic target for balancing emotion regulation in children with neurodevelopmental conditions.

Individual differences in intracortical inhibition predict action control when facing emotional stimuli.

Efficient inhibitory control in the context of prepotent actions is vital. However, such action inhibition may be profoundly influenced by affective states. Interestingly, research indicates that action control can be either impaired or improved by emotional stimuli. Thus, a great deal of confusion surrounds our knowledge of the complex dynamics subtending emotions and action control. Here, we aimed to investigate whether negative stimuli, even when non-consciously presented and task-irrelevant, can affect action control relative to neutral stimuli. Additionally, we tested whether individual differences in intracortical excitability may predict action control capabilities. To address these issues, we asked participants to complete a modified version of the Stop Signal Task (SST) in which fearful or neutral stimuli were subliminally presented before the go signals as primes. Moreover, we assessed participants' resting-state corticospinal excitability, short intracortical inhibition (SICI), and intracortical facilitation (ICF). Results demonstrated better action control capabilities when fearful stimuli were subliminally presented and interindividual SICI predicted stronger action inhibition capabilities. Taken together, these results shed new light on the intricate dynamics between action, consciousness, and motor control, suggesting that intracortical measures can be used as potential biomarkers of reduced motor inhibition in research and clinical settings.

A Bibliometric Analysis of Knowledge Dynamics and Open Innovation Process

Abstract The article investigates from an analytical perspective the relationship between knowledge dynamics and open innovation and their influence on today's business environment. The present study starts from the premise that the development of a fluid and constant flow of knowledge exchange outside the organization influences the processes of open innovation. Allowing the rapid adaptation of organizations to the new effervescent demands of the market and consumers. The addition brought by this paper represents a conceptual expansion of the need to understand the possible implications of external and internal knowledge, of a rational, emotional, or spiritual nature, on the processes of development of new strategies, products, and services. There is no substantial information available in the specialized literature about the two concepts, which highlights the need to develop more qualitative and quantitative research in this direction. Using the bibliometric analysis with VOSviewer software, the paper presents a series of results that can be further developed and analyzed. The first perspective highlighted by this study is the potential of emotional, rational, and spiritual knowledge to improve relationships with consumers as a result of implementing a constant flow of communication. This fact is supported by the symbiotic relationship between the role of knowledge dynamics in encouraging the exchange of knowledge between consumers and organizations that stimulates an open, transparent communication environment focused on continuous learning. The study also emphasizes the involvement of collaboration, adaptability, and dynamic capabilities to explore how knowledge dynamics influence and stimulate innovative culture.

The relationship between burnout syndrome and emotional intelligence in anesthesiologists during the COVID-19 pandemic: A cross-sectional study

Background Burnout, a type of long-lasting work-related stress, is highly prevalent among health professionals. It includes dimensions of emotional exhaustion, depersonalization and low professional achievement. Emotional intelligence is the ability to accurately perceive, evaluate, and express emotions, to perceive and/or produce feelings that facilitate thought, to understand emotion and acquire emotional knowledge, and to control emotions in order to promote emotional and intellectual growth. Among the extensive literature on burnout, no studies have measured its prevalence among anesthesiologists in Brazil during the COVID-19 pandemic. Studies on the association between emotional intelligence and burnout are also scarce in this population. The aim of this study was to describe the prevalence of burnout in anesthesiologists at a hospital during the COVID-19 pandemic and to assess its association with emotional intelligence. Methods This cross-sectional study was conducted in a large private hospital in southern Brazil. A non-probabilistic convenience sample of anesthesiologists was selected from a hospital's clinical staff. Via Google Forms, participants responded to an anonymous self-applied self-explanatory questionnaire with sections on sociodemographic data, burnout (Maslach Burnout Inventory), and emotional intelligence (Wong and Law's Emotional Intelligence Scale). Descriptive analysis of the variables was performed and the association between burnout and emotional intelligence was evaluated using the Pearson or Spearman correlation coefficient, depending on data distribution. Results A burnout prevalence of 8.1% was found, as well as a strong negative correlation between total burnout scores and emotional intelligence. Conclusions According to the regression analysis, emotional intelligence can be considered an independent factor associated with this outcome.

Community Engagement, The Context for Teachers’ Work-Efficiency? A Tism Approach

Purpose: The main purpose of this research work is to find the scope of enhancing the teachers’ work-efficiency through the logical linkages of emotional exhaustion, attitude, knowledge management (KM), and community-engagement. Methods: With a qualitative research approach, i.e.: Total Interpretive Structural Modeling (TISM), this study tried to explore the intricate relationships between the aforesaid components in Indian context. With the overview of community engagement having its significant importance in educational settings, research problem is defined, which guided for extensive literature review, the core part of TISM. The study utilizes fundaments of ISM along with the contextual relationships to reach the hierarchical model of TISM to visually represent the relationships between the identified factors, reflecting their driving power and dependency power. Results & discussions: This study established the complete interpretations of the linkages among variables through developed model of TISM. Further, this research-work shows how the identified factors collectively contribute to teachers’ overall work-efficiency, where online customer-engagement and offline customer-engagement forms the context for the attitude and KM, and emotional exhaustion that are in turn leads to work-efficiency of teachers. Implications of the study: This study highlights the scopes for comprehensive strategies to enhance work-efficiency of teachers through fostering positive attitudes and effective KM on the ground of community engagement, where emotional exhaustion is managed adequately.

Emotion-specific vocabulary and its relation to emotion understanding in children and adolescents

ABSTRACT Among children and adolescents, emotion understanding relates to academic achievement and higher well-being. This study investigates the role of general and emotion-specific language skills in children’s and adolescents’ emotion understanding, building on previous research highlighting the significance of domain-specific language skills in conceptual development. We employ a novel inventory (CEVVT) to assess emotion-specific vocabulary. The study involved 10–11-year-old children (N = 29) and 16–17-year-old adolescents (N = 28), examining their emotion recognition and knowledge of emotion regulation strategies. Results highlight the ongoing development of emotion-specific vocabulary across these age groups. Emotion recognition correlated with general vocabulary in the younger group. In the older age group, emotion recognition was related to emotion-specific vocabulary size, but this effect only became apparent when controlling for the depth of emotion-specific vocabulary. Against expectation, there were no significant contributions of general or emotion-specific vocabulary to knowledge of emotion regulation strategies in either age group. These findings enhance our comprehension of the nuanced interplay between language and emotion across developmental stages.

Beyond learning with cold machine: interpersonal communication skills as anthropomorphic cue of AI instructor

Prior research has explored the impact of diverse anthropomorphic interventions on the effectiveness of AI (artificial intelligence) instructors. However, the exploration of interpersonal communication skills (e.g., self-disclosure) as anthropomorphic conversational cues for AI instructors is rare. Considering the positive impact of the self-disclosure of human instructors and guided by the social penetration theory (Altman & Taylor, 1973) and computers are social actors (CASA) paradigm (Nass & Moon, 2000), this study explores the role of self-disclosure by AI instructors and the mediating role of emotional attachment between AI instructors’ self-disclosure and students’ learning experiences (learning interest and knowledge gain). Additionally, it examines the differences in students’ emotional attachment, learning interest, and knowledge gain between AI and human instructors. Through a 2 (AI instructor vs. human instructor) × 2 (self-disclosure: yes or no) experiment, this study concluded that 1) consistent with human instructors, self-disclosure by AI instructors led to higher emotional attachment, learning interest, and knowledge gain; 2) emotional attachment played an important mediating role in AI instructor self-disclosure and students’ learning interest and knowledge gain; and 3) in the context of self-disclosure, students exhibited similar levels of emotional attachment to both AI and human instructors, with no significant differences observed. Regarding learning outcomes, while students demonstrated a greater interest in learning during courses taught by AI instructors, the difference in knowledge gained from AI and human instructors was not significant. The results of this study contribute to the understanding of the anthropomorphic cues of AI instructors and provide recommendations and insights for the future use of AI instructors in educational settings.

Aspect-Level Sentiment Analysis of Customer Reviews Based on Neural Multi-task Learning

In the era of big data, major e-commerce platforms are facing the challenge of an exponential growth in the number of user comments. Effectively utilizing these comments has become an urgent issue. Traditional manual statistical methods are no longer able to meet the demands for accuracy and real-time analysis. The rise of artificial intelligence-based text mining techniques provides a new approach to address this problem. By building deep learning analysis models, it is possible to uncover user preferences and product characteristics, helping businesses proactively adjust sales strategies, improve product and service quality, and achieve precise marketing. Text sentiment analysis is one of the important research directions in the field of text mining. Its basic idea is to transform subjective texts with emotional color into structured data, and then use machine learning, deep learning, and other artificial intelligence technologies to extract emotional features and discover knowledge patterns. This article proposes a deep learning-based sentiment analysis model, which includes a shared sentiment prediction layer used to transfer emotional knowledge between different aspect categories and alleviate the problem of insufficient data. The model consists of two parts: the Aspect Category Detection (ACD) classifier based on attention mechanism and the Aspect Category Sentiment Analysis (ACSA) classifier. The ACD part generates word weights using attention mechanism, while the ACSA part predicts the sentiment of words and combines weights to determine the sentiment of aspect categories within sentences.

Multi-modal sarcasm detection based on emotion perception and cross-modality attention fusion

Sarcasm is a rhetorical device commonly used in social media and is prevalent on some social platforms, such as Twitter and Reddit, to dismiss, criticize or ridicule people or events using metaphors and exaggeration. With the rapid growth of social media and internet technology, the way people express their emotions and feelings is not limited to text. Therefore, a multi-modal sarcasm detection task is crucial to understanding people’s real feelings and beliefs. However, most existing models often use implicit fusion and do not significantly align the emotions between modalities explicitly, neglecting the significant role of emotional words in sarcasm detection. In this paper, a model was proposed based on emotion perception and cross-modality attention fusion for multi-modal sarcasm detection. Specifically, an external emotional knowledge was introduced for emotional information enhancement. In addition, the dual-channel BERT-based module and cross-modality interaction fusion were proposed based on an attention mechanism. The experimental results on a public multi-modal sarcasm detection dataset based on Twitter demonstrate the superiority of the proposed model.

AdMISC: Advanced Multi-Task Learning and Feature-Fusion for Emotional Support Conversation

The emotional support dialogue system is an emerging and challenging task in natural language processing to alleviate people’s emotional distress. Each utterance in the dialogue has features such as emotion, intent, and commonsense knowledge. Previous research has indicated subpar performance in strategy prediction accuracy and response generation quality due to overlooking certain underlying factors. To address these issues, we propose Advanced Multi-Task Learning and Feature-Fusion for Emotional Support Conversation (AdMISC), which extracts various potential factors influencing dialogue through neural networks, thereby improving the accuracy of strategy prediction and the quality of generated responses. Specifically, we extract features affecting dialogue through dynamic emotion extraction and commonsense enhancement and then model strategy prediction. Additionally, the model learns these features through attention networks to generate higher quality responses. Furthermore, we introduce a method for automatically averaging loss function weights to improve the model’s performance. Experimental results using the emotional support conversation dataset ESConv demonstrate that our proposed model outperforms baseline methods in both strategy label prediction accuracy and a range of automatic and human evaluation metrics.

Pragmatic controlled trial of a school-based emotion literacy program for 8- to 10-year-old children: study protocol

BackgroundMental disorders are common in childhood, but many young people do not receive adequate professional support. Help-seeking interventions may bridge this treatment gap, however, there is limited research on interventions for primary-school children. This study aims to evaluate the effectiveness of an emotion literacy program at increasing literacy, reducing stigma, and promoting help-seeking in children aged 8–10 years.Methods and analysisA two-arm pragmatic cluster-controlled trial will compare Thriving Minds, an emotion literacy program for middle primary school children, to a wait-list control condition. Children aged 8–10 years will be recruited from approximately 12 schools (6 intervention schools/6 wait-list control) to participate in Thriving Minds via direct invitation by the program delivery service. Allocation to the intervention condition will be pragmatically, by school. Children will receive the intervention over two 50-minute sessions, across two weeks. Using story books and interactive discussion, the program aims to develop children’s knowledge of their own and other’s emotional experiences and emotion regulation strategies (self-care and help-seeking). The primary outcome is help-seeking intentions. Secondary outcomes include help-seeking knowledge, attitudes, and behaviours, emotion knowledge and attitudes, and stigma. Children will complete surveys at pre-intervention, post-intervention (one week after the program) and 12-week follow-up. Additional satisfaction data will be collected from teachers in intervention schools via surveys (post-intervention and 3-month follow-up) and semi-structured interviews (after follow-up), and selected children via focus groups (12-week follow-up). Analyses will compare changes in help-seeking intentions relative to the waitlist control condition using mixed-model repeated-measures analyses to account for clustering within schools.DiscussionWith demonstrated effectiveness, this universal emotion literacy program for promoting help-seeking for mental health could be more widely delivered in Australian primary schools, providing a valuable new resource, contributing to the mental health of young people by improving help-seeking for early mental health difficulties.Trial registrationAustralian New Zealand Clinical Trials Registry, ACTRN12623000910606 Registered on 24 August 2023.

Olfactory training improves emotion matching ability in 6–9 years old children — preliminary evidence

AbstractEmotion knowledge involves the ability to recognize and express emotions and understand emotional processes. The neural substrates of emotion knowledge include i.a. the amygdala, orbitofrontal cortex, and anterior cingulate cortex. These structures are also involved in processing olfactory stimuli and their volume and functional activity have been shown to increase after a period of regular olfactory stimulation (olfactory training, OT). We verified if OT will improve one aspect of emotion knowledge — the ability to match emotional facial expressions. Eighty‐three children (39 boys) aged 6–9 years were randomly assigned either to an OT group (OTG) that smelled a set of four odors (lemon, cloves, eucalyptus, rose) twice a day for 12 weeks or to a placebo group that performed the training with odorless stimuli. Children in the OTG (n = 40) matched emotional facial expressions significantly better after OT as compared with their baseline score. This effect was not present in the placebo group (n = 43) whose scores remained the same after OT.Practical applicationsThis novel finding suggests the potential of olfactory stimulation in supporting emotion knowledge in children and bridges recent findings in sensory studies, psychophysiology, and emotional development. Further studies are necessary to delineate which aspects of emotion knowledge might be enhanced by OT. In future, OT might be potentially included in programs designed for groups with specific emotion knowledge deficits.

Benchmarking Cyber Harassment Dialogue Comprehension through Emotion-Informed Manifestations-Determinants Demarcation

In the digital age, cybercrimes, particularly cyber harassment, have become pressing issues, targeting vulnerable individuals like children, teenagers, and women. Understanding the experiences and needs of the victims is crucial for effective support and intervention. Online conversations between victims and virtual harassment counselors (chatbots) offer valuable insights into cyber harassment manifestations (CHMs) and determinants (CHDs). However, the distinction between CHMs and CHDs remains unclear. This research is the first to introduce concrete definitions for CHMs and CHDs, investigating their distinction through automated methods to enable efficient cyber-harassment dialogue comprehension. We present a novel dataset, Cyber-MaD that contains Cyber harassment dialogues manually annotated with Manifestations and Determinants. Additionally, we design an Emotion-informed Contextual Dual attention Convolution Transformer (E-ConDuCT) framework to extract CHMs and CHDs from cyber harassment dialogues. The framework primarily: a) utilizes inherent emotion features through adjective-noun pairs modeled by an autoencoder, b) employs a unique Contextual Dual attention Convolution Transformer to learn contextual insights; and c) incorporates a demarcation module leveraging task-specific emotional knowledge and a discriminator loss function to differentiate manifestations and determinants. E-ConDuCT outperforms the state-of-the-art systems on the Cyber-MaD corpus, showcasing its potential in the extraction of CHMs and CHDs. Furthermore, its robustness is demonstrated on the emotion cause extraction task using the CARES_CEASE-v2.0 dataset of suicide notes, confirming its efficacy across diverse cause extraction objectives. Access the code and data at 1. https://www.iitp.ac.in/~ai-nlp-ml/resources.html#E-ConDuCT-on-Cyber-MaD, 2. https://github.com/Soumitra816/Manifestations-Determinants.

Face and context integration in emotion inference is limited and variable across categories and individuals

The ability to make nuanced inferences about other people’s emotional states is central to social functioning. While emotion inferences can be sensitive to both facial movements and the situational context that they occur in, relatively little is understood about when these two sources of information are integrated across emotion categories and individuals. In a series of studies, we use one archival and five empirical datasets to demonstrate that people could be integrating, but that emotion inferences are just as well (and sometimes better) captured by knowledge of the situation alone, while isolated facial cues are insufficient. Further, people integrate facial cues more for categories for which they most frequently encounter facial expressions in everyday life (e.g., happiness). People are also moderately stable over time in their reliance on situational cues and integration of cues and those who reliably utilize situation cues more also have better situated emotion knowledge. These findings underscore the importance of studying variability in reliance on and integration of cues.