Human Emotions Research Articles

Anger and Art Ambivalent emotion in art

The present study investigates the depiction of anger in Western visual art, highlighting the paradox of this emotion: its inherent unpleasantness and repulsiveness versus its artistic representation. The authors examine historical transformations in the expression of anger and the mechanisms that render its depiction effective in art. Despite being a fundamental human emotion encountered from birth, anger is surprisingly scarce in Western visual art. Historical artworks often depict actions resulting from anger rather than capturing its raw emotional expression. Kelly Grovier's essay "Art of Feeling: Why We Should Celebrate Anger" posits that the rarity of anger’s depiction may stem from its classification as a deadly sin by early Christian teachings, which stigmatized the emotion. However, significant works such as Delacroix's "Medea" and Gentileschi's "Judith" juxtapose violent acts with serene facial expressions, underscoring a disconnect between action and emotional display. The repulsiveness and transformative impact of anger on human appearance make it a challenging subject for art. Yet, works like Cabanel's "Fallen Angel" and Gérôme's "Truth Coming Out of Her Well" explore this transformation, employing beauty to attract and distortion to repulse, thereby creating a Medusa-like effect. This duality engages viewers and evokes mixed emotions, which enhances an artwork's impact. Furthermore, anger can drive creative innovation, as demonstrated in works by Munch, Picasso, and Kahlo, where personal and societal grievances fuel artistic expression. However, prolonged anger may lead to destructive creativity, emphasizing the complex role of anger in art and its potential for both innovation and hostility. This multifaceted exploration underscores anger’s unique, albeit limited, place in visual arts and its dual capacity to repel and inspire.

A facial and vocal emotion recognition system based on deep learning

The traditional teaching mode, mainly characterized by "cramming" instruction, often overlooks the absorption of knowledge by students during the teaching process. Even in recent years, the emerging "flipped classroom" model heavily relies on teachers' experience and expertise, making it challenging to quantify students' classroom learning states. Among young teachers lacking teaching experience, the replication of excellent teaching models faces difficulties. With the rapid development of artificial intelligence technology, deep learning and other AI techniques are increasingly applied to people's lives. Additionally, emotion computing technology is also becoming more sophisticated. In the field of education, the use of AI technology holds the potential to help teachers systematically and comprehensively assess teaching quality, promoting the sharing of high-quality educational resources nationally and globally. Existing emotion detection technologies often focus on single techniques such as image recognition or natural language processing, resulting in low accuracy in discerning human emotions and making it difficult to accurately identify emotional changes in complex scenarios such as classrooms. Furthermore, there is a lack of comprehensive emotional statistical analysis methods for audio and visual data. In light of these, we have designed and implemented a multi-modal emotion recognition and analysis system. Through testing in classroom settings, this system has the potential to assist classroom teaching and enhance teaching quality.

Emotion topology: extracting fundamental components of emotions from text using word embeddings.

This exploratory study examined the potential of word embeddings, an automated numerical representation of written text, as a novel method for emotion decomposition analysis. Drawing from a substantial dataset scraped from a Social Media site, we constructed emotion vectors to extract the dimensions of emotions, as annotated by the readers of the texts, directly from human language. Our findings demonstrated that word embeddings yield emotional components akin to those found in previous literature, offering an alternative perspective not bounded by theoretical presuppositions, as well as showing that the dimensional structure of emotions is reflected in the semantic structure of their text-based expressions. Our study highlights word embeddings as a promising tool for uncovering the nuances of human emotions and comments on the potential of this approach for other psychological domains, providing a basis for future studies. The exploratory nature of this research paves the way for further development and refinement of this method, promising to enrich our understanding of emotional constructs and psychological phenomena in a more ecologically valid and data-driven manner.

Using Social Robotics to Identify Educational Behavior: A Survey

The advancement of social robots in recent years has opened a promising avenue for providing users with more accessible and personalized attention. These robots have been integrated into various aspects of human life, particularly in activities geared toward students, such as entertainment, education, and companionship, with the assistance of artificial intelligence (AI). AI plays a crucial role in enhancing these experiences by enabling social and educational robots to interact and adapt intelligently to their environment. In social robotics, AI is used to develop systems capable of understanding human emotions and responding to them, thereby facilitating interaction and collaboration between humans and robots in social settings. This article aims to present a survey of the use of robots in education, highlighting the degree of integration of social robots in this field worldwide. It also explores the robotic technologies applied according to the students’ educational level. This study provides an overview of the technical literature in social robotics and behavior recognition systems applied to education at various educational levels, especially in recent years. Additionally, it reviews the range of social robots in the market involved in these activities. The objects of study, techniques, and tools used, as well as the resources and results, are described to offer a view of the current state of the reviewed areas and to contribute to future research.

Design of Chinese painting style classification model based on multi-layer aggregation CNN

This study delves deeply into exploring the artistic value of traditional Chinese painting (TCP) and aims to bridge the gap between its fundamental characteristics and the realm of human emotions. To achieve this, a novel convolutional neural network (CNN)-based classification model for TCP emotions is proposed. By thoroughly analyzing the distinct emotional mapping relationships inherent in TCP, a comprehensive framework is developed. Notably, emotional feature regions are accurately extracted using image saliency, and a multi-layer aggregation recalibrated emotional feature module is seamlessly integrated into the CNN network structure. This integration strengthens the activation of features that significantly influence TCP emotions. Moreover, a method of multi-category weighted activation localization is skillfully employed to classify Chinese painting emotions within the CMYK (cyan magenta yellow black) color space. The empirical results convincingly demonstrate that our algorithm surpasses existing approaches such as VGG-19, GoogLeNet, ResNet-50, and WSCNet in the task of TCP emotion recognition, achieving an impressive accuracy of 92.36%, the largest error is 0.191. This improvement signifies the advancements made by our model in accurately capturing and understanding the emotional nuances within TCP. By outperforming previous methods, our research contributes to the convergence of multimedia technology and cultural education.

KECERDASAN EMOSIONAL DAN PENDIDIKAN AGAMA ISLAM (Telaah Atas Pemikiran Darwis Hude)

Abstract: The purpose of this study is to analyze Darwis Hude's thoughts on emotional intelligence and describe its relevance to the relevance of Islamic Religious Education. This study uses library research and focuses on studying emotional intelligence according to Darwis Hude which is contained in his book Emotions: Religious-Psychological Exploration of Human Emotions in the Qur'an. The analysis technique used is content analysis. The findings of this study are the relevance of emotional intelligence according to Darwis Hude, namely directing educators to understand emotional intelligence that will be able to control facial expressions, voice, attitude and behavior when carrying out the teaching and learning process in the classroom. The deeper a person studies his emotions, the deeper a person's faith. Because he knows that the emotions in him will produce something good if managed properly.

Sarcasm Detection Based on Sentiment Analysis of Audio Corpus Using Deep Learning

With the rapid progress in digitalization, hundreds of services and applications have begun to depend on human-machine communication, primarily voice-based. As technology advances, it has become increasingly imperative to develop systems that can discern sophisticated emotions from humans, like sarcasm. Despite research that has been conducted on the detection and analysis of speech signals to try and understand emotion, the detection of sarcasm, which is often not overtly expressed, is quite far from something that has received the attention it deserves in recent years. It plays a very important role in any utterance, searching to identify the psychology, mood, or even health behind it. Hence, it does give interactions with humans a more human-like flavor while raising the feeling of understanding human emotions. This article tries to identify sarcasm in speech using audio data derived from real-world, spontaneous, monolingual corpora. In this classification process, a deep learning classifier known as CNN-LSTM model is used. Results of the study showed that a robust combination between feature extraction through convolutional layers and sequential learning through LSTM layers can identify intricate speech patterns in sarcasm. Experimented and validated in terms of performance, this model shows the model to be very good at discriminating between sarcastic and no sarcastic speech, thus promoting it for more extensive use in various applications related to sentiment analysis and in human-computer interaction applications. The results show that this system provides far much closer approximations to human interaction styles, but its impact would extend into a wide area from customer services, monitoring mental health, and even AI-driven communication systems. It is a monolingual and spontaneous corpus that will open the gates for further work and development down the line and possibly extend to multilingual and more diversified speech contexts, thus fine-tuning accuracy in practical scenarios of sarcasm detection.

Modeling Emotion Recognition System from Facial Images Using Convolutional Neural Networks

Emotion classification is the process of identifying human emotions. Implementing technology to help people with emotional classification is considered a relatively popular research field. Until now, most of the work has been done to automate the recognition of facial cues (e.g., expressions) from several modalities (e.g., image, video, audio, and text). Deep learning architecture such as Convolutional Neural Networks (CNN) demonstrates promising results for emotion recognition. The research aims to build a CNN model while improving accuracy and performance. Two models are proposed in the research with some hyperparameter tuning followed by two datasets and other existing architecture that will be used and compared with the proposed architecture. The two datasets used are Facial Expression Recognition 2013 (FER2013) and Extended Cohn-Kanade (CK+), both of which are commonly used datasets in FER. In addition, the proposed model is compared with the previous model using the same setting and dataset. The result shows that the proposed models with the CK+ dataset gain higher accuracy, while some models with the FER2013 dataset have lower accuracy compared to previous research. The model trained with the FER2013 dataset has lower accuracy because of overfitting. Meanwhile, the model trained with CK+ has no overfitting problem. The research mainly explores the CNN model due to limited resources and time.

Emotion Recognition Using EEG Signals and Audiovisual Features with Contrastive Learning.

Multimodal emotion recognition has emerged as a promising approach to capture the complex nature of human emotions by integrating information from various sources such as physiological signals, visual behavioral cues, and audio-visual content. However, current methods often struggle with effectively processing redundant or conflicting information across modalities and may overlook implicit inter-modal correlations. To address these challenges, this paper presents a novel multimodal emotion recognition framework which integrates audio-visual features with viewers' EEG data to enhance emotion classification accuracy. The proposed approach employs modality-specific encoders to extract spatiotemporal features, which are then aligned through contrastive learning to capture inter-modal relationships. Additionally, cross-modal attention mechanisms are incorporated for effective feature fusion across modalities. The framework, comprising pre-training, fine-tuning, and testing phases, is evaluated on multiple datasets of emotional responses. The experimental results demonstrate that the proposed multimodal approach, which combines audio-visual features with EEG data, is highly effective in recognizing emotions, highlighting its potential for advancing emotion recognition systems.

Ascending Vagal Sensory and Central Noradrenergic Pathways Modulate Retrieval of Passive Avoidance Memory in Male Rats.

Visceral feedback from the body is often subconscious, but plays an important role in guiding motivated behaviors. Vagal sensory neurons relay "gut feelings" to noradrenergic (NA) neurons in the caudal nucleus of the solitary tract (cNTS), which in turn project to the anterior ventrolateral bed nucleus of the stria terminalis (vlBNST) and other hypothalamic-limbic forebrain regions. Prior work supports a role for these circuits in modulating memory consolidation and extinction, but a potential role in retrieval of conditioned avoidance remains untested. To examine this, adult male rats underwent passive avoidance conditioning. We then lesioned gut-sensing vagal afferents by injecting cholecystokinin-conjugated saporin toxin (CSAP) into the vagal nodose ganglia (Experiment 1), or lesioned NA inputs to the vlBNST by injecting saporin toxin conjugated to an antibody against dopamine-beta hydroxylase (DSAP) into the vlBNST (Experiment 2). When avoidance behavior was later assessed, rats with vagal CSAP lesions or NA DSAP lesions displayed significantly increased conditioned passive avoidance. These new findings support the view that gut vagal afferents and the cNTSNA-to-vlBNST circuit play a role in modulating the expression/retrieval of learned passive avoidance. Overall, our data suggest a dynamic modulatory role of vagal sensory feedback to the limbic forebrain in integrating interoceptive signals with contextual cues that elicit conditioned avoidance behavior.

People’s English in the Poetry of Mzi Mahola and Vonani Bila

Black poets and various wordsmiths in South Africa played a critical role in liberating the country. Several of these artists wrote in indigenous languages, but during the 1960s and 1970s some protest poets expressed their opposition to oppression in English. These artists also played a pivotal role in ensuring that the outside world became aware of apartheid suppression. Other critics have, however, questioned the role of the English language for the masses that surrounded these artists. It is also important to understand how these artists perceived their role in their society as English poets. The article focuses on two South African poets, Mzi Mahola and Vonani Bila, whose recent poetry examines the current struggles, joys, and happenings in their communities. The article focuses on how these two poets use English to express their experiences. Furthermore, the themes explored in the article reveal the commonalities that may exist among “black English poets” in South Africa. More than three decades after the demise of apartheid some themes have pervaded their writings as new struggles have emerged. Furthermore, People’s English continues to be a vital tool in expressing black and human emotions in post-apartheid South Africa.

Behavioral strategy in evolution: A review and conceptual framework

Behavioral strategy integrates psychology with strategic management theory and practice, offering realistic insights into human cognition, emotions, and social behavior in strategic management. Yet behavioral strategy's antecedents, mechanisms, consequences, and moderators and their interconnectedness and future directions remain unclear. We explore this field's development and current state based on a systematic literature review of 241 articles. We develop a conceptual framework using a coevolutionary perspective and a socially situated cognition approach, which captures essential behavioral strategy elements and dynamics. We advance the field by emphasizing multilevel coevolving dynamics and the interplay of cognition and emotions in shaping strategic behavior. Furthermore, our framework situates cognition within social contexts. We propose an expanded research agenda for the field that highlights artificial intelligence's potential role in enhancing behavioral strategy and the connection between heuristics and nudge frameworks.

TRACING EXISTENTIALIST THEMES IN THE FILM THE PIGEON

Cinema, with its power to reflect and reproduce reality, is an art closely related to human experience. A vast spectrum of human emotions and ideas, from social issues to personal experiences, can be seen in films. In addition to its ability to reproduce and reflect reality, cinema has a close relationship with philosophy. By presenting philosophical concepts with the help of its unique apparatuses, cinema gives viewers the opportunity to experience and question abstract ideas. In this way, cinema encourages them to think, question and look at the world from a different perspective. Among these perspectives, existentialism, as a philosophical movement, paves the way to explore individual's freedom, responsibility and the necessity of creating one's own meaning. Cinema benefits largely from existentialism because it presents a suitable framework to depict individuals’ struggle to exist in this world. This study explores how cinema portrays existentialist themes, focusing on the film The Pigeon to examine the connection between individuals and the social world. A combination of descriptive and thematic analyses was performed to uncover existential themes in the film, such as "the absurd", "alienation", "unhomeliness", "anxiety", "forlornness" and "authenticity". The analysis concluded that these recurring themes are prevalent throughout the film. The film clearly shows that the protagonist is pressured by social norms to conform. However, he chooses to follow his own path and finds an authentic way to live his life.

A Contrastive Study of the Verb “Make” in Selected English and Arabic Religious Texts

To be determined by the context, the verb make is considered one of the multi- meaning verbs which conveys several meanings. Picking out the appropriate meaning of the verb make is a problem. The current study is restricted to analyze various linguistic manifestations of the verb make in English and Arabic. It is also confined with showing points of similarity and difference between the two languages in their uses of the verb make in some selected religious texts. It is hypothesized that "make" in English is tactful and diplomatic while in Arabic is solemn and unflattering. It is suggested that "make" has an appreciative meaning in one language and a passive one in another. It is also expected that linguistic structure plays a role in determining the suitable meaning of "make" in both languages. The findings show that "make" in Arabic texts is more powerful than English "make" which tends to be passionate and tenderness. It is capable of mimicking human emotions and able to coexist with bitterness of reality. It is also concluded that there is a positive correlation between tenses of the verb "make", in both languages, and the idea concerned.

The Role of Intuitive Anger in Public Punitiveness: An Investigation Into the Influence of Anger on People’s Reactions to Crime

Anger is a fundamental human emotion characterized by opposition, impatience, and dissatisfaction. It is usually triggered during particular events and could result in a variety of physiological and behavioral reactions (DeCelles et al., 2020). This study focused on the role of anger in people’s reactions to crime. Specifically, it investigated intuitive anger, a quick and automatic negative emotional response that opposes principles of punishment but still contributes to punitiveness. To explore the influence of intuitive anger on the tendency to impose punishment or penalties on others, this study used facial electromyography (fEMG) and collected data from students at McGill University in Canada (N= 40). The present study’s repeated-measures experimental design would enable testing of the hypothesis that when making punitive decisions for alleged «stereotypical criminals,» individuals will exhibit greater responses of intuitive anger. It was anticipated that the display of images depicting stereotypical criminals would result in a substantial rise in instinctive anger response compared to images of atypical criminals. This is because the former are often perceived as lacking warmth (meaning, a lack of friendliness, kindness, and approachability) (Fiske et al., 2002). Therefore, this approach suggests potential variations in emotional responses based on the type of image presented.

Interpretation of Human Emotion: An Implementation of Compassion through Karuna Rasa in Manjula Padmanabhan’s Lights Out

Interpretation of Human Emotion: An Implementation of Compassion through Karuna Rasa in Manjula Padmanabhan’s Lights Out

EmoiPlanner: Human emotion and intention aware socially acceptable robot navigation in human‐centric environments

AbstractThe deployment of robots in human‐centric environments has significantly increased in recent years. It is crucial for robots to navigate human environments while understanding social norms and personal boundaries to ensure a harmonious coexistence between humans and robots. A socially aware robot should be capable of interpreting and responding appropriately to human cues, expressions, and intentions, thereby fostering trust and confidence among humans. However, prior studies were insufficient or unable to address the navigation challenges in human‐populated environments, as they perceive people as obstacles rather than social agents. Recent studies have utilized proxemic areas that are present in interpersonal interactions for human‐robot interaction scenarios, but they have enforced consistent proxemic areas for social robot navigation. This approach fails to fully capture the highly sophisticated behaviour and preferences of humans. Therefore, we propose a psychologically‐based adaptive proxemic area that fluctuates based on the human's emotional state. Furthermore, we integrate this feature into a reinforcement learning‐based social navigation framework, making our navigation framework robust to the unpredictable affections of humans. Additionally, our navigation framework includes human intention prediction to approximate the future proxemic area, thereby avoiding interference with the path to be taken by individuals. We have named our framework the Human Emotion and Intention Aware Path Planner (EmoiPlanner). Our framework has been subjected to case studies involving realistic crowd navigation scenarios, and the results indicate that it enables robots to navigate through crowds without causing discomfort to pedestrians who exhibit stochastic behaviours and emotional states, while also ensuring efficient path planning.

HiMul-LGG: A hierarchical decision fusion-based local–global graph neural network for multimodal emotion recognition in conversation

Emotion recognition in conversation (ERC) is a vital task that requires deciphering human emotions through analysis of contextual and multimodal information. However, extant research on ERC concentrates predominantly on investigating multimodal fusion while overlooking the model’s constraints in dealing with unimodal representation discrepancy and speaker dependencies. To address the aforementioned problems, this paper proposes a Hierarchical decision fusion-based Local–Global Graph Neural Network for multimodal ERC (HiMul-LGG). HiMul-LGG employs a hierarchical decision fusion strategy to ensure feature alignment across modalities. Moreover, HiMul-LGG also adopts a local–global graph neural network architecture to reinforce inter-modality and intra-modality speaker dependency. Additionally, HiMul-LGG utilizes a cross-modal multi-head attention mechanism to promote interplay between modalities. We evaluate HiMul-LGG on two emotion recognition datasets, IEMOCAP and MELD, where HiMul-LGG outperforms existing methods. The results of the ablation study also imply the effectiveness of the proposed hierarchical decision fusion strategy and local–global structure of Graph construction.

The Lord Is Kind-Hearted And Cannot See The Poor: Social Reflections On The Film”Return To Dust”

Chinese cinema has always played an important role in spreading culture and transmitting values. As a kind of audio-visual media, it needs to be able to reflect social reality, moral concepts as well as cultural values in a profound way. However, in China, which has a strict film censorship system, the production and dissemination of films are strictly controlled and restricted by the government censorship system. There is a film Return to Dust, which created heat through many self-media, such as XiaoHongShu and DOUYIN, before its release, in which the previews showed real rural literary scenes that attracted wide attention. After its release, the social aspect of the film explored the deep-seated human emotions and regional issues, and a month later, the film was taken off the shelves, instantly triggering a wide-ranging discussion on censorship standards and artistic freedom [1]. Return to Dust, as a literary film, is sufficiently rich in cultural connotation and social significance for the audience. The film uses linear storytelling to show the current situation of the rural underclass in Northwest China during the four seasons of the year, the social ills and the complexity of human nature, which triggers the audience to think about "suffering". However, it is worth noting that although the film shows the "suffering", it also shows the warmth of the two underclass people, i.e. the goodness and beauty of human nature. However, such films with sensitive social issues are often restricted by the Chinese government's censorship. Exploring the reasons why Return to Dust has not been accepted by the modern Chinese government is not only a critical reflection on the censorship results of the film, but also a profound analysis of the censorship standards, value orientations, and the ideology of the censors behind the censorship system of Chinese cinema

Signs and symptoms in hospitalized children and adolescents' triggering nurses' awareness – A qualitative study across Denmark and Norway

BackgroundAssessment of signs and symptoms in hospitalized children presents unique challenges due to the children's age-related differences, such as vital signs and the broad range of medical conditions that affects children. Early detection of clinical changes in children is crucial to prevent deterioration, and while standardized tools exist, there is a growing recognition of the need to consider subjective factors based on experienced nurses' knowledge and intuition. ObjectiveTo explore which signs and symptoms, apart from vital signs, that trigger nurses' concern regarding deterioration of hospitalized children and adolescents. DesignThis study used a descriptive qualitative design. SettingsThe study was conducted at three pediatric departments in Denmark and a nursing department of a university in Norway, offering post graduate education programs for health care professions working with children and adolescents throughout Norway. ParticipantsA total sample of 29 registered nurses with varying levels of experience participated. MethodFour focus group interviews were used to collect data and analyzed with inductive content analysis approach. ResultsNurses' knowledge about children's clinical conditions is influenced by the nurses experience, their use of senses like touching the child with their hands, and the use of various approaches. Information from parents about the child's normal behavior are considered valuable. These sources of information, often difficult to verbalize, might be referred to as intuition or “gut feeling” and often guides the nurses' actions when vital signs appear normal, and nurses rely on their senses to assess the child's condition. Specific indicators triggering concern include changes in respiration, circulation, level of consciousness, and facial expressions. Challenges arise from nighttime assessments, interactions with parents, the presence of electronic devices, and children's ability to compensate. Clinical experience is a significant factor in nurses' ability to recognize changes in in the child's condition. ConclusionThis study highlights the multifaceted nature of nurses' assessments of clinical conditions in hospitalized children. Nurses draw on their experiences, intuition, and interactions with parents to complement vital signs-based assessments. Their intuition, or “gut feeling” serves as a valuable tool when vital signs do not fully capture the child's clinical status. Specific signs and symptoms that trigger nurses' concern, along with the challenges they face, contribute to a comprehensive understanding of the complexity of assessing children's clinical conditions. These findings, emphasize the role of nurses in early recognition of clinical deterioration in hospitalized children and the need for assessments that go beyond vital signs. Tweetable abstractBoth objective assessments and intuitive clinical judgment play an important role in identifying potential deterioration in pediatric patients.