Emotion knowledge: Further exploration of a prototype approach

On (Im)Patience: A New Approach to an Old Virtue

Academic AbstractPatience has been of great interest to religious scholars, philosophers, and psychological scientists. Their efforts have produced numerous insights but no cohesive theoretical approach to understanding the broad set of experiences people label as patience. I propose a novel view of patience, one that departs from but ties together existing approaches. Grounded in theories of emotion and emotion regulation, I propose impatience as a discrete emotion triggered by an objectionable delay of some sort, and patience (as a state or process rather than a virtue) as a form of emotion regulation that targets the subjective experience and outward expression of impatience. I propose a number of predictors and consequences of patience and impatience and provide initial evidence for many of the theory's tenets. This theoretical approach, the process model of patience, reveals coherence across varied fields and methodologies and generates novel, testable, and timely questions for future patience scholars.Public Abstract"Patience is a virtue" is a familiar exhortation, and patience has been of great interest to religious scholars, philosophers, and psychological scientists. Their efforts have produced numerous insights but no cohesive theoretical approach to understanding the broad set of experiences people label as patience. This paper proposes an entirely novel view of patience, one that departs from but ties together existing approaches. I propose that impatience is an emotion, triggered by a frustrating delay of some sort, and patience captures the various ways people try to deal with their experience of impatience. I also propose that various aspects of the situation and the person combine to determine the intensity of impatience and the effectiveness of patience. Finally, I discuss the implications of a theoretical model, the process model of patience, for both scientific inquiry and issues of social justice, which are often fueled by appropriate experiences of impatience.

The shock of Awe experience to our soul is more directly on cognitive well-being than affective well-being

Previous research has demonstrated that the experience of awe can alleviate negative emotions, such as stress related to life and career, consequently enhancing overall happiness. Drawing from the broaden-and-build theory of positive emotions, the mechanism through which awe mitigates stress and enhances happiness lies in its capacity to restructure an individual's original cognitive framework and foster a more open-minded approach to problem-solving. This, in turn, facilitates the cultivation of both physical and mental resources, including the enhancement of psychological resilience, thereby empowering individuals to better rebound from adversity and pressure. The study seeks to validate this perspective. In this study, 342 Chinese college students (awe group, pleasant group and neutral group) were investigated to test the effects of awe on cognitive well-being and affective well-being using a recall priming task paradigm. Results indicated that: (1) compared with pleasant and neutral groups, awe experience not only had a direct effect on cognitive well-being (life satisfaction), but it also had a significant indirect effect on cognitive well-being through a mediating variable - resilience. However, (2) awe experience had no direct effect on affective well-being (emotional balance), although the mediating effect of resilience was significant. This suggested that awe, as a transcendent positive experience, might have different effects or mechanism on individuals' cognition and emotion evaluation.

Integrating emotional vocabulary in EFL education: a model for enhancing emotional intelligence in pre-service EFL teachers

This study investigates the role of emotional vocabulary in fostering emotional intelligence (EI) among pre-service EFL teachers, focusing on the Headway series. The general objective was to quantify, categorize, and classify emotion vocabulary across proficiency levels and to develop a systematic teaching model to enhance EI in pre-service teachers. A mixed-methods approach was employed: quantitative analysis identified and categorized emotional vocabulary using established lexicons, and qualitative thematic analysis aligned this vocabulary with key EI components such as self-awareness, emotional regulation, and empathy. To develop the systematic teaching model, a design-based research methodology was utilized, incorporating iterative refinement based on empirical findings and expert feedback. Grounded in Goleman's Emotional Intelligence Theory, the study revealed a progressive increase in emotional vocabulary, with more complex emotions introduced at advanced levels. Positive emotions were more frequent at beginner levels, while negative and neutral emotions increased at higher stages, supporting self-regulation and empathy development. The systematic teaching model proposed in the study addresses key EI components such as self-awareness, social skills, and emotional regulation by scaffolding emotional vocabulary instruction across proficiency levels. This model provides a structured framework to equip educators with the emotional and linguistic tools necessary for effective classroom management and enhanced student outcomes. This research holds pedagogical implications for teacher training programs, recommending that emotional vocabulary and EI be integrated into pre-service education to improve classroom management and student outcomes.

What emotions does music express? Structure of affect terms in music using iterative crowdsourcing paradigm

Music is assumed to express a wide range of emotions. The vocabulary and structure of affects are typically explored without the context of music in which music is experienced, leading to abstract notions about what affects music may express. In a series of three experiments utilising three separate and iterative association tasks including a contextualisation with typical activities associated with specific music and affect terms, we identified the plausible affect terms and structures to capture the wide range of emotions expressed by music. The first experiment produced a list of frequently nominated affect terms (88 out of 647 candidates), and the second experiment established and confirmed multiple factor structures, ranging from 21, to 14, and 7 dimensions. The third experiment compared the terms with external datasets looking at discrete emotions and emotion dimensions, which verified the 7-factor structure and identified a compact 4-factor structure. These structures of affects expressed by music did not conform to music-induced emotion structures, nor could they be explained by basic emotions or affective circumplex. The established affect structures were largely positive and contained concepts such as "romantic" and "free", and terms such as "in love", "dreamy", and "festive" that have rarely featured in past research.

Informational ecosystems partially explain differences in socioenvironmental conceptual associations between U.S. American racial groups

Social groups represent a collective identity defined by a distinct consensus of concepts (e.g., ideas, values, and goals) whose structural relationship varies between groups. Here we set out to measure how a set of inter-concept semantic associations, comprising what we refer to as a concept graph, covaries between established social groups, based on racial identity, and how this effect is mediated by information ecosystems, contextualized as news sources. Group differences among racial identity (278 Black and 294 white Americans) and informational ecosystems (Left- and Right- leaning news sources) are present in subjective judgments of how the meaning of concepts such as healthcare, police, and voting relate to each other. These racial group differences in concept graphs were partially mediated by the bias of news sources that individuals get their information from. This supports the idea of groups being defined by common conceptual semantic relationships that partially arise from shared information ecosystems.

Do we feel colours? A systematic review of 128 years of psychological research linking colours and emotions

Colour is an integral part of natural and constructed environments. For many, it also has an aesthetic appeal, with some colours being more pleasant than others. Moreover, humans seem to systematically and reliably associate colours with emotions, such as yellow with joy, black with sadness, light colours with positive and dark colours with negative emotions. To systematise such colour-emotion correspondences, we identified 132 relevant peer-reviewed articles published in English between 1895 and 2022. These articles covered a total of 42,266 participants from 64 different countries. We found that all basic colour categories had systematic correspondences with affective dimensions (valence, arousal, power) as well as with discrete affective terms (e.g., love, happy, sad, bored). Most correspondences were many-to-many, with systematic effects driven by lightness, saturation, and hue ('colour temperature'). More specifically, (i) LIGHT and DARK colours were associated with positive and negative emotions, respectively; (ii) RED with empowering, high arousal positive and negative emotions; (iii) YELLOW and ORANGE with positive, high arousal emotions; (iv) BLUE, GREEN, GREEN-BLUE, and WHITE with positive, low arousal emotions; (v) PINK with positive emotions; (vi) PURPLE with empowering emotions; (vii) GREY with negative, low arousal emotions; and (viii) BLACK with negative, high arousal emotions. Shared communication needs might explain these consistencies across studies, making colour an excellent medium for communication of emotion. As most colour-emotion correspondences were tested on an abstract level (i.e., associations), it remains to be seen whether such correspondences translate to the impact of colour on experienced emotions and specific contexts.

Moral Association Graph: A Cognitive Model for Automated Moral Inference

Automated moral inference is an emerging topic of critical importance in artificial intelligence. The contemporary approach typically relies on language models to infer moral relevance or moral properties of a concept. This approach demands complex parameterization and costly computation, and it tends to disconnect with existing psychological accounts of moralization. We present a simple cognitive model for moral inference, Moral Association Graph (MAG), inspired by psychological work on moralization. Our model builds on word association network for inferring moral relevance and draws on rich psychological data. We demonstrate that MAG performs competitively to state-of-the-art language models when evaluated against a comprehensive set of data for automated inference of moral norms and moral judgment of concepts, and in-context moral inference. We also show that our model yields interpretable outputs and is applicable to informing short-term moral change.

The function of timbre in the perception of affective intentions: Effect of enculturation in different musical traditions

Timbre has been identified as a potential component in the communication of affect in music. Although its function as a carrier of perceptually useful information about sound source mechanics has been established, less is understood about whether and how it functions as a carrier of information for communicating affect in music. To investigate these issues, listeners trained in Chinese and Western musical traditions were presented with Phrases, Measures, and Notes of recorded excerpts interpreted with a variety of affective intentions by performers on instruments from the two cultures. Results showed greater accuracy and more extreme responses in Chinese musician listeners and lowest accuracy in nonmusicians suggesting that musical training plays a role in listeners' decoding of affective intention. Responses were more differentiated and more accurate with more musical information. Excerpts were also analyzed to determine acoustic features that are correlated with timbre characteristics. Temporal, spectral, and spectrotemporal attributes were consistently used in judging affective intent in music, suggesting purposeful use of these properties by listeners. Comparison between listeners' use of acoustic features reveals a greater number of shared features between Western musicians and nonmusicians compared to Chinese musicians for valence, although the three groups shared more features for arousal. How timbre is utilized in musical communication appears to be different across musical traditions, and valence responses seem to be more culture-specific and arousal responses more similar across cultures.

More than meets the gut: a prototype analysis of the lay conceptions of intuition and analysis

Using a prototype approach, we assessed people's lay conceptions of intuition and analysis. Open-ended descriptions of intuition and analysis were generated by participants (Study 1) and resulting exemplars were sorted into features subsequently rated in centrality by independent participants (Study 2). Feature centrality was validated by showing that participants were quicker and more accurate in classifying central (as compared to peripheral) features (Study 3). Centrality ratings suggested a single-factor structure describing analysis but revealed that participants held lay conceptions of intuition as involving two different types of processes: (1) as an automatic, affective, and non-logical processing, and (2) as a holistic processing that can assist in problem-solving. Additional analyses showed that the centrality ratings of intuition's facets were predicted by participants' self-reported intuitive style, suggesting intuition is differently perceived by intuitive and non-intuitive people. We discuss the implications of these results for the study of intuition and analysis.

Joyful growth vs. compulsive hedonism: A meta-analysis of brain activation on romantic love and addictive disorders

Due to the similarities in behavioral characteristics between romantic love and addictive disorders, the concept of being "addicted to someone" transcends mere literary metaphor, expanding perspectives on the study of romantic love and inspiring interventions for addiction. However, there has been a lack of studies systematically exploring the similarities and differences between romantic love and addiction at the neural level. In this study, we conducted an extensive literature search, incorporating 21 studies on romantic love and 28 on addictive disorders, focusing on fMRI research utilizing the cue reactivity paradigm. Using Activation Likelihood Estimation, we examined the similarities and differences in the neural mechanisms underlying love and addiction. The results showed that the anterior cingulate cortex (ACC) exhibited both shared and distinct activation clusters between romantic love and addictive disorders. Furthermore, ventromedial prefrontal cortex (VMPFC) was more frequently activated in romantic love than in addictive disorders, while greater activation within the posterior cingulate cortex (PCC) was found in addictive disorder compared with romantic love. We discussed that the activation of ACC and VMPFC may symbolize self-expansion, a process that characterizes the development of romantic love, contributing to a more enriched self. Our study suggests that while romantic love and addictive disorders share a common neural foundation, the discernible differences in their neural representations distinguish them as joyful growth versus compulsive hedonism.

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.

Depressive self-focus bias following failure: an eye-tracking study among individuals with clinical depression

Objective

Depression is often characterized by a persistent sense of failure. Cognitive theories of depression suggest that depressed individuals may exhibit a maladaptive cognitive style, characterized by increased self-focus following personal failure. The validity of this proposition, however, is yet to be fully examined. This study aimed to identify the relation between symptoms in major depressive disorder and increased self-focus in failure situations.

Methods

This clinical study involved a cohort of 30 patients diagnosed with and treated for depression. We used an eye-tracking paradigm to observe and analyze gaze direction - indicative of either self-focus or self-avoidance - after remembering a significant failure event.

Results

Contrary to the maladaptive cognitive style hypothesis, a majority of the depressed participants demonstrated an inclination towards self-avoidance following failure. Nevertheless, approximately 30% of the patient group - those with the highest scores of guilt, punishment, and self-blame - displayed a self-focused attentional bias post-failure.

Conclusions

The presence of a maladaptive self-focusing style may be confined to severely depressed patients with high levels of guilt, punishment, and self-blame. These findings could have substantial clinical implications, as attention bias modification interventions could be particularly beneficial for this subgroup of patients.

Experimentally manipulated anger activates implicit cognitions about social hierarchy

A correlational pilot study (N = 143) and an integrative data analysis of two experiments (total N = 377) provide evidence linking anger to the psychology of social hierarchy. The experiments demonstrate that the experience of anger increases the psychological accessibility of implicit cognitions related to social hierarchy: compared to participants in a control condition, participants in an anger-priming condition completed word stems with significantly more hierarchy-related words. We found little support for sex differences in the effect of anger on implicit hierarchy-related cognition; effects were equivalent across male and female participants. Findings fit with functionalist evolutionary views of anger suggesting that anger may motivate the use of dominance to strive for high social rank in group hierarchies. Implications for downstream behaviour, including aggression and negotiation, are discussed.

Collective UK nostalgia predicts a desire to leave the European Union

Collective nostalgia is an emotion experienced when one sentimentally recalls events or things related to a particular social identity. We investigated the relationship between collective nostalgia about the United Kingdom (UK) and UK citizens' desire to leave the European Union (EU). We collected data of UK citizens twice prior to the UK's official withdrawal from the European Union (N = 347 and N = 240) and once afterwards (N = 236). Cross-sectional and longitudinal analysis, utilizing cross-lagged panel models, supported the hypothesis that collective UK nostalgia increased the desire to leave the European Union. We additionally hypothesized that the relationship between these variables would be mediated positively by ties to UK citizens and negatively by ties to EU citizens. Exploratory and longitudinal analysis, however, indicated that strength of ties to UK and EU citizens predicts levels of collective UK nostalgia which, in turn, predicts desire to leave the European Union. Specifically, ties to UK citizens were associated with increased collective nostalgia and a desire to leave the EU and ties to EU citizens were associated with reduced collective nostalgia and a desire to re-join the European Union. We discuss the implications of the findings as well as making suggestions for future studies.

Discovering the sensory, emotional, and interactive experiences of a place

This article proposes a data collection technique for describing experiences of a built environment. Besides the experiences of the visual and physical aspects of the place, this technique helps describe the sensory, bodily, emotional, interactive, and social experiences occurring during the human-environment encounter. The enabling technique presented is called Reactions and Actions Description Survey (RADES). It employs 120 images depicting people going through different situations involving all the senses, showing expressions related to positive and negative emotions, and realizing varied activities. Forty-five participants visited the esplanade in the exterior of a historic building called Obispado. The case study is located on a hill and is a scenic viewpoint of Monterrey, Mexico. The participants answered the RADES and the Environmental Description Survey (ENVIDES), which focuses on describing the qualities of the place and the appraisals with which it is experienced. The comments about the experiences of the place obtained through both surveys were grouped into 133 categories. Qualitative and quantitative data about the experiences of the place were obtained through both techniques. A quantitative analysis of the data was realized since the participants not only described their experiences with words but also indicated numerically the intensity of such experiences. Spearman correlations between the experiences were calculated, and a general map of the experiences of the place was created through multidimensional scaling analysis (MDS). The study revealed the connections between the elements and qualities of the site and the views with specific positive and negative experiences occurring during the visit. Furthermore, MDS allowed the discovery of 10 dimensions of environmental experience-pleasure/displeasure, high/low arousal, dominance/submissiveness, knowing/inhabiting, environment/self, higher/lower cognition, spatiality/materiality, states/processes, natural/built, and visual/sensory. The presented techniques and the findings obtained through them can assist architects in recognizing valuable environmental features for the design of livable spaces.

Do breaks in online gambling affect neuropsychological arousal? Conceptual approach and lessons learned from the TESSA-pilot trial

Introduction

Mandatory breaks have been discussed as a harm reduction strategy in the context of gambling for several years, but their effectiveness remains unclear. The TESSA pilot study examines the association of physiological arousal (PA) and mandatory breaks during gambling with an aim to conceptualize the framework for a subsequent randomized controlled trial.

Material and methods

In a one-armed experimental pilot study 28 participants engaged in a simulated online slot game with mandatory breaks. PA, disentangled into fear, anger, joy, attraction, balance, and retraction, was continuously monitored via skin conductivity and skin temperature. The occurrence of PA in distinct phases (phase 1: initiation, phase 2: pre-break, phase 3: post-break) was contrasted by multilevel logistic regression.

Results

Fear and attraction did not change. Compared to phase 1, anger (OR = 0.698; p = 0.015) and joy (OR = 0.714; p = 0.032) were less likely in phase 2, with joy also being less likely in phase 3 (OR = 0.690; p = 0.023). Balance was more likely in phase 2 (OR = 5.073; p < 0.0001) than in phase 1 and less likely in phase 3 (OR = 0.348; p < 0.0001) whilst retraction declined from phase to phase.

Discussion

Mandatory breaks appear suited to offset changes in PA response evolving during gambling, but a sustained effect on initial PA levels should not to be expected. However, to sensitively judge the role of breaks additional framework conditions that impact on gambling behavior (e. g. wins/losses) should be considered.

DOLPHIN: A Mixed-Methods Study of a Parenting App to Nurture the First Two Years of Life in the Indian Context

Background

The first two years of life are critical for brain development. Experiences and exposures during this period can have long-term effects on an individual's health. Therefore, we aim to develop a program for new parents in the Indian context to help them understand their developing infant's needs and provide the best possible care grounded in traditional practices to ensure healthy developmental outcomes.

Materials and Methods

The program was developed using the exploratory-confirmatory framework grounded in qualitative methods-(a) collection of empiric evidence base by conducting a thorough literature review, (b) tacit experience, and (c) focus group discussions with relevant stakeholders. Picture-based content (one picture per day for two years) was created, and the program was expert-validated. A web-based application was developed to make it available to parents, and the program was translated into three regional languages to improve its reach. A telephonic user feedback survey was carried out, and descriptive statistics were used to present the findings from the survey.

Results

DOLPHIN stands for "Developing Opportunities of Learning for Parents to Help Infant Nurture." Over 600 parents accessed the program. Feedback is positive in the domains of parental satisfaction and user-friendliness.

Discussion

The program primarily focuses on ensuring appropriate sensorimotor stimulation and meeting the socioemotional needs of the growing infant through the first two years, emphasizing healthy nutrition and hygiene to ensure holistic development. Therefore, its approach is health-promotive and disease-preventive. It incorporates traditional child-rearing practices of India rich in stimulation, promoting secure attachment, and incidental learning: "readiness."

Conclusion

The DOLPHIN program demonstrates a promising approach to supporting new parents in nurturing their infants during the critical first two years of life. With positive feedback and a focus on traditional practices and evidence-based content, it holds potential as a health-promotive and preventive intervention for holistic child development in the Indian context.

Refuting Six Misconceptions about Romantic Love

Scientific research on romantic love has been relatively sparse but is becoming more prevalent, as it should. Unfortunately, several misconceptions about romantic love are becoming entrenched in the popular media and/or the scientific community, which hampers progress. Therefore, I refute six misconceptions about romantic love in this article. I explain why (1) romantic love is not necessarily dyadic, social, or interpersonal, (2) love is not an emotion, (3) romantic love does not just have positive effects, (4) romantic love is not uncontrollable, (5) there is no dedicated love brain region, neurotransmitter, or hormone, and (6) pharmacological manipulation of romantic love is not near. To increase progress in our scientific understanding of romantic love, I recommend that we study the intrapersonal aspects of romantic love including the intensity of love, that we focus our research questions and designs using a component process model of romantic love, and that we distinguish hypotheses and suggestions from empirical findings when citing previous work.

A meta-analytic review of anger management activities that increase or decrease arousal: What fuels or douses rage?

Anger is an unpleasant emotion that most people want to get rid of. Some anger management activities focus on decreasing arousal (e.g., deep breathing, mindfulness, meditation), whereas others focus on increasing arousal (e.g., hitting a bag, jogging, cycling). This meta-analytic review, based on 154 studies including 184 independent samples involving 10,189 participants, tested the effectiveness of both types of activities. The results indicated that arousal-decreasing activities decreased anger and aggression (g = -0.63, [-0.82, -0.43]), and the results were robust. Effects were stable over time for participants of different genders, races, ages, and cultures. Arousal-decreasing activities were effective in students and non-students, in criminal offenders and non-offenders, and in individuals with and without intellectual disabilities. Arousal-decreasing activities were effective regardless of how they were delivered (e.g., digital platforms, researchers, therapists), in both group and individual sessions, and in both field and laboratory settings. In contrast, arousal-increasing activities were ineffective overall (g = -0.02, [-0.13, 0.09]) and were heterogenous and complex. These findings do not support the ideas that venting anger or going for a run are effective anger management activities. A more effective approach for managing anger is "turning down the heat" or calming down by engaging in activities that decrease arousal.

A comprehensive dataset for sentiment and emotion classification from Bangladesh e-commerce reviews

In the rapidly evolving domain of e-commerce, analyzing customer feedback through reviews is crucial, particularly for understanding and enhancing consumer experience in the Bangladeshi market. Our comprehensive dataset, derived from two Bangladeshi e-commerce platforms, Daraz and Pickaboo, features a diverse collection of reviews in both Bengali and English, covering a broad range of products. These reviews are not only rich in linguistic variety but also encapsulate a spectrum of emotions, some even conveyed through emojis, offering a deep dive into consumer sentiment. Expert annotators have meticulously examined and categorized each review, classifying emotions into five distinct types - Happiness, Sadness, Fear, Anger, and Love - and sentiments into Positive (Happiness, Love) and Negative (Sadness, Anger, Fear) categories. This level of detailed annotation enables precise assessments of customer emotions and preferences, which are essential for evaluating and improving existing product offerings. Moreover, the insights gleaned from this dataset are invaluable for guiding future product development and uncovering new opportunities in the dynamic Bangladeshi market. Ultimately, this dataset not only serves as a significant resource for sentiment analysis using natural language processing (NLP) techniques but also contributes valuable insights into the unique consumer behavior patterns in Bangladesh, enriching the NLP community's understanding of diverse market dynamics.

Emotional culture and humor in organizations: A social-functional approach

Adopting a social-functionalist theoretical lens, this review examines emotional culture and its relation to discrete emotions such as joviality and humor-supportive or "joking" organizational cultures. We propose four primary pathways through which humor influences emotional culture in organizations and social units: (1) creating and defining emotional culture through "bottom-up" affective mechanisms, (2) a "top-down" normative function that promotes or inhibits humor through cultural values, norms, and traditions of organizational life, (3) a maintenance function, whereby humor corrects emotional culture norm violations, and (4) a link to positive work outcomes via a reciprocal feedback loop. We also describe negative consequences of humor for emotional culture, highlight unanswered questions in the literature, and suggest future research opportunities, including a comprehensive new framework.

What We Can Learn About Emotion by Talking With the Hadza

Emotions are often thought of as internal mental states centering on individuals' subjective feelings and evaluations. This understanding is consistent with studies of emotion narratives, or the descriptions people give for experienced events that they regard as emotions. Yet these studies, and contemporary psychology more generally, often rely on observations of educated Europeans and European Americans, constraining psychological theory and methods. In this article, we present observations from an inductive, qualitative analysis of interviews conducted with the Hadza, a community of small-scale hunter-gatherers in Tanzania, and juxtapose them with a set of interviews conducted with Americans from North Carolina. Although North Carolina event descriptions largely conformed to the assumptions of eurocentric psychological theory, Hadza descriptions foregrounded action and bodily sensations, the physical environment, immediate needs, and the experiences of social others. These observations suggest that subjective feelings and internal mental states may not be the organizing principle of emotion the world around. Qualitative analysis of emotion narratives from outside of a U.S. (and western) cultural context has the potential to uncover additional diversity in meaning-making, offering a descriptive foundation on which to build a more robust and inclusive science of emotion.

Experienced Love: An Empirical Account

This article presents new evidence on the prevalence, dynamics, and hedonic correlates of experienced love from data describing the emotion, well-being, and time use of a diverse sample of 3,867 U.S. adults every half hour for 10 days (N = 1.12 million) supplemented by a hedonic snapshot of an additional 7,255 adults. The findings allude to the seemingly functional and adaptive nature of love and to similarities across binary gender-men and women reported comparable degrees of (passionate) partner love overall, elevated partner love after prolonged same-day separations, substantially elevated well-being in love's presence, and reduced (but not extinguished) partner love in mature marital cohorts. The gender differences that were found-women reported more child love than men, and men exhibited a less pronounced reduction in partner love across cohorts-are also consistent with functional accounts of love that recognize the varying role of men and women in the formation and sustenance of relationships.

Weighting Assessment of the Effect of Chinese State-Changing Words on Emotions

Past studies of sentiment analysis have mainly applied algorithms based on vocabulary categories and emotional characteristics to detect the emotionality of text. However, the collocation of state-changing words and emotional vocabulary affects emotions. For example, adverbs of degree strengthen emotions, and negative adverbs reverse emotions. This study investigated the weighted effect of state-changing words on emotion. The research material comprised 73 state-changing words that were collocated with four emotions: happiness, sadness, fear, and anger. A total of 84 participants participated in the vocabulary assessment. The results revealed that state-changing words could be classified into four types: intensifying, weakening, neutralizing, and reversing. In a comparison of the weighting factors among emotions, the weighting effect of the same state-changing word in the positive emotion category was particularly evident. The results could serve as a reference for follow-up studies on detecting emotions in text.

Emotional Prototypicality Ratings for 636 Chinese Words: A Database of Chinese Words with Affective Information

Exemplars of concepts vary in their degree of prototypicality. This is also true for emotion concepts. This study presents prototypicality ratings for a large set of Chinese words. The database contains 636 potential Chinese emotion words (i.e., words that directly express particular emotions, like " happy" and " sad"), from different grammatical categories. Native Chinese speakers rated the words in terms of emotional prototypicality. The database also contains values for valence, arousal, and emotionality. The analyses of the ratings revealed that 502 out of 636 words had a high prototypicality value (value equal to or above three on a 1-to-5 scale), the most prototypical words being negative and high-arousal words. The analyses also indicated that the emotional prototypicality of a word was positively related to both arousal and emotionality, and negatively related to valence. Among these variables, arousal was the most important contributor. Similar results have been found in studies conducted in other languages. This will be a useful resource for researchers interested in studying emotion words in the Chinese language and for those interested in cross-linguistic comparisons.

Toward a General Framework of Biased Reasoning: Coherence-Based Reasoning

A considerable amount of experimental research has been devoted to uncovering biased forms of reasoning. Notwithstanding the richness and overall empirical soundness of the bias research, the field can be described as disjointed, incomplete, and undertheorized. In this article, we seek to address this disconnect by offering "coherence-based reasoning" as a parsimonious theoretical framework that explains a sizable number of important deviations from normative forms of reasoning. Represented in connectionist networks and processed through constraint-satisfaction processing, coherence-based reasoning serves as a ubiquitous, essential, and overwhelmingly adaptive apparatus in people's mental toolbox. This adaptive process, however, can readily be overrun by bias when the network is dominated by nodes or links that are incorrect, overweighted, or otherwise nonnormative. We apply this framework to explain a variety of well-established biased forms of reasoning, including confirmation bias, the halo effect, stereotype spillovers, hindsight bias, motivated reasoning, emotion-driven reasoning, ideological reasoning, and more.

The Paradox of Love: A Historical Exploration of Western Philosophical Perspectives on Love, Exclusion, and Liberatory Potential

The present work tracks some of the most well-known thinkers on love in the Western philosophical tradition, where various theories emerge, conflict, converge, and fade away. Given that many questions about its nature have persisted for centuries, love's identity appears unsettled. Due to its unresolved identity, love might be best understood as a paradox existing between its resistance to definition and yet commonly recognized and experienced. The other central thread stemming from these philosophers of love is how the history of its theorizing constructed a restrictive notion that commonly excluded women from the experience. Offering a natural rebuttal to the history of exclusion promoted by these prominent thinkers is bell hooks' notion of an expansive and healing love that possessed the capacity to realize more fulfilling relationships and a compassionate society. This paper concludes with thoughts on love's liberatory nature, its capacity to create personal meaning, and its identity as a paradox without attempting to define it.

Development and Validation of an Ability Measure of Emotion Understanding: The Core Relational Themes of Emotion (CORE) Test

Emotion understanding (EU) ability is associated with healthy social functioning and psychological well-being. Across three studies, we develop and present validity evidence for the Core Relational Themes of Emotions (CORE) Test. The test measures people's ability to identify relational themes underlying 19 positive and negative emotions. Relational themes are consistencies in the meaning people assign to emotional experiences. In Study 1, we developed and refined the test items employing a literature review, expert panel, and confusion matrix with a demographically diverse sample. Correctness criteria were determined using theory and prior research, and a progressive (degrees of correctness) paradigm was utilized to score the test. In Study 2, the CORE demonstrated high internal consistency and a confirmatory factor analysis supported the unidimensional factor structure. The CORE showed evidence of convergence with established EU ability measures and divergent relationships with verbal intelligence and demographic characteristics, supporting its construct validity. Also, the CORE was associated with less relational conflict. In Study 3, the CORE was associated with more adaptive and less maladaptive coping and higher well-being on multiple indicators. A set of effects remained, accounting for variance from a widely used EU test, supporting the CORE's incremental validity. Theoretical and methodological contributions are discussed.

Multilabel multiclass sentiment and emotion dataset from indonesian mobile application review

Reviews are a person's way of expressing feedback on something in the form of criticism and ideas. Reviews of mobile apps are a type of user feedback that focuses on the performance and look of a mobile application and is typically featured on the download page of a mobile application, such as in the Apps Store. Because it comprises a person's feelings and emotions, whether they are joyful, sad, hostile, or indifferent toward a mobile application, the review data is textual and may be gathered and utilized as material for creating a textual dataset. This work creates a multi-label multi-class Indonesian-language dataset based on public reviews of mobile applications with sentiment and emotional values. Another factor supporting the creation of this dataset is the fact that there is still a limited number of textual datasets based on the Indonesian language that are multi-label multiclass for performing sentiment analysis tasks, particularly those linked to text classification tasks. The data generated by this research was cleaned and handled during the pre-processing step and was annotated with 3 sentiments, namely positive, negative, and neutral, as well as 6 emotions, namely anger, fear, sad, happy, love, and neutral.

Using social media and personality traits to assess software developers' emotional polarity

Although human factors (e.g., cognitive functions, behaviors and skills, human error models, etc.) are key elements to improve software development productivity and quality, the role of software developers' emotions and their personality traits in software engineering still needs to be studied. A major difficulty is in assessing developers' emotions, leading to the classic problem of having difficulties understanding what cannot be easily measured. Existing approaches to infer emotions, such as facial expressions, self-assessed surveys, and biometric sensors, imply considerable intrusiveness on developers and tend to be used only during normal working periods. This article proposes to assess the feasibility of using social media posts (e.g., developers' posts on Twitter) to accurately determine the polarity of emotions of software developers over extended periods in a non-intrusive manner, allowing the identification of potentially abnormal periods of negative or positive sentiments of developers that may affect software development productivity or software quality. Our results suggested that Twitter data can serve as a valid source for accurately inferring the polarity of emotions. We evaluated 31 combinations of unsupervised lexicon-based techniques using a dataset with 79,029 public posts from Twitter from sixteen software developers, achieving a macro F1-Score of 0.745 and 76.8% of accuracy with the ensemble comprised of SentiStrength, Sentilex-PT, and LIWC2015_PT lexicons. Among other results, we found a statistically significant difference in tweets' polarities posted during working and non-working periods for 31.25% of the participants, suggesting that emotional polarity monitoring outside working hours could also be relevant. We also assessed the Big Five personality traits of the developers and preliminarily used them to ponder the polarities inferences. In this context, Openness, Conscientiousness, and Extraversion were frequently related to neutral and positive posts, while Neuroticism is associated with negative posts. Our results show that the proposed approach is accurate enough to constitute a simple and non-intrusive alternative to existing methods. Tools using this approach can be applied in real software development environments to support software team workers in making decisions to improve the software development process.

Unconscious and conscious acceptance downregulate aggressive behavior: Mediating role of anger regulation

Social exclusion can induce negative emotions and aggression. While previous studies have investigated the effect of trait acceptance on emotional experience and aggression during social exclusion, it is still unclear how different forms of acceptance strategy can downregulate negative emotions and whether this potential reduction of negative emotions should mediate the effect of acceptance on aggression. To address these questions, 100 participants were recruited and randomly divided into three groups: control group (CG, N = 33), conscious acceptance group (CAG, N = 33) and unconscious acceptance group (UAG, N = 34). Negative emotions were induced by the cyberball game and measured by the modified PANAS. Aggressive behavior was assessed by the hot sauce allocation task. Results showed that anger, rather than other negative emotions, mediated the effect of acceptance on aggressive behavior. Conscious and unconscious acceptance both effectively regulated anger, hurt feelings and aggressive behavior during social exclusion. Compared to conscious acceptance, unconscious acceptance was associated with less reduction of positive emotion and had a better effect on reducing sadness. These findings highlight the advantage of applying unconscious acceptance strategy to regulating social exclusion-induced emotions for the purpose of reducing aggressive behavior.

Valuing the emotions of leadership learning experience in nursing education

AIM

This paper argues that a greater understanding of the role of emotions in experiencing leadership, the impact of role models and cultures of the workplace and profession, may enable further development for effective leadership development at undergraduate level and beyond.

BACKGROUND

Leadership has gained prominence as a necessary skill in nursing literature and policy, linking its importance to patient safety, working cultures, resilience and emotional labour globally. Viewed as essential in many undergraduate nursing programmes and a requirement by professional regulators, there is a globally agreed acceptance of its importance. Despite this, the focus on evaluating and researching the effectiveness of leadership learning and through experiences of students in contexts of learning remain limited. This paper presents a discussion on the importance of experiences of leadership, exploring the emotional impact and how enabling reflexivity and critical analysis can be integrated in education. An approach is proposed for nursing education where the emotional impact of experiencing leadership is given significance. Experiences of leadership in practice and educational learning in higher education should allow students to reflect and conceptualise experience, aligning educational contexts of learning. Acknowledgement of emotional experience and pragmatism provides opportunity to strengthen evidence and knowledge and establish leadership as a concept of value in the profession from an early stage.

DESIGN

A critical theoretical discussion paper METHODS: Based on a narrative inquiry study, drawing on theory and philosophies of emotions in education and leadership from 1907 to 2023 RESULTS: Acknowledgement of emotional experience and pragmatism provides opportunity to strengthen evidence and establish leadership as a concept of value in the profession from an early stage.

CONCLUSIONS

Placing value on the experience of leadership by reflexivity and pragmatic, experiential approaches to learning can align educational contexts of learning and focus on effective leadership learning for the nursing profession.

TWEETABLE ABSTRACT

Pragmatic approaches and reflexivity rationalise emotional experiences of leadership and encourage critical thinking and learning.

The Meso-Expression Test (MET): A Novel Assessment of Emotion Perception

Emotion perception is a primary facet of Emotional Intelligence (EI) and the underpinning of interpersonal communication. In this study, we examined meso-expressions-the everyday, moderate-intensity emotions communicated through the face, voice, and body. We theoretically distinguished meso-expressions from other well-known emotion research paradigms (i.e., macro-expression and micro-expressions). In Study 1, we demonstrated that people can reliably discriminate between meso-expressions, and we created a corpus of 914 unique video displays of meso-expressions across a race- and gender-diverse set of expressors. In Study 2, we developed a novel video-based assessment of emotion perception ability: The Meso-Expression Test (MET). In this study, we found that the MET is psychometrically valid and demonstrated measurement equivalence across Asian, Black, Hispanic, and White perceiver groups and across men and women. In Study 3, we examined the construct validity of the MET and showed that it converged with other well-known measures of emotion perception and diverged from cognitive ability. Finally, in Study 4, we showed that the MET is positively related to important psychosocial outcomes, including social well-being, social connectedness, and empathic concern and is negatively related to alexithymia, stress, depression, anxiety, and adverse social interactions. We conclude with a discussion focused on the implications of our findings for EI ability research and the practical applications of the MET.

Emotion Recognition Based on Electroencephalogram Using Semi-supervised Generative Adversarial Network

This paper proposes the use of Semi-supervised Generative Adversarial Network (SGAN) to take advantage of the large amount of unlabeled electroencephalogram (EEG) spectrogram data in improving the classifier's accuracy in emotion recognition. The use of SGAN led the discriminator network to not just learn in a supervised fashion from the small amount of labeled data to distinguish among the different target classes, but also make use of the true unlabeled data to distinguish them from the synthetic ones generated by the generator network. This additional ability to distinguish true and fake samples forces the network to focus only on features that are present on a true sample to distinguish the classes, thereby improving generalization and overall accuracy. An ablation study is devised, where the SGAN classifier is compared to a mere discriminator network without the GAN architecture. The 80% : 20% validation method was employed to classify the EEG spectrogram of 50 participants gathered by Kaohsiung Medical University into two emotion labels in the valence dimension: positive and negative. The proposed method achieved an accuracy of 84.83% given only 50% labeled data, which is not just better than the baseline discriminator network which achieved 83.5% accuracy, but is also better than many previous studies at accuracies around 78%. This demonstrates the ability of SGAN in improving discriminator network's accuracy by training it to also distinguish between the unlabeled true sample and synthetic data.Clinical Relevance- The use of EEG in emotion recognition has seen growing interest due to its ease of access. However, the large amount of labeled data required to train an accurate model has been the limiting factor as databases in the area of emotion recognition with EEG is still relatively small. This paper proposes the use of SGAN to allow using large amount of unlabeled EEG data to improve the recognition rate.

Experiments on real-life emotions challenge Ekman's model

Ekman's emotions (1992) are defined as universal basic emotions. Over the years, alternative models have emerged (e.g. Greene and Haidt 2002; Barrett 2017) describing emotions as social and linguistic constructions. The variety of models existing today raises the question of whether the abstraction provided by such models is sufficient as a descriptive/predictive tool for representing real-life emotional situations. Our study presents a social inquiry to test whether traditional models are sufficient to capture the complexity of daily life emotions, reported in a textual context. The intent of the study is to establish the human-subject agreement rate in an annotated corpus based on Ekman's theory (Entity-Level Tweets Emotional Analysis) and the human-subject agreement rate when using Ekman's emotions to annotate sentences that don't respect the Ekman's model (The Dictionary of Obscure Sorrows). Furthermore, we investigated how much alexithymia can influence the human ability to detect and categorise emotions. On a total sample of 114 subjects, our results show low within subjects agreement rates for both datasets, particularly for subjects with low levels of alexithymia; low levels of agreement with the original annotations; frequent use of emotions based on Ekman model, particularly negative one, in people with high levels of alexithymia.

An Assessment of In-the-Wild Datasets for Multimodal Emotion Recognition

Multimodal emotion recognition implies the use of different resources and techniques for identifying and recognizing human emotions. A variety of data sources such as faces, speeches, voices, texts and others have to be processed simultaneously for this recognition task. However, most of the techniques, which are based mainly on Deep Learning, are trained using datasets designed and built in controlled conditions, making their applicability in real contexts with real conditions more difficult. For this reason, the aim of this work is to assess a set of in-the-wild datasets to show their strengths and weaknesses for multimodal emotion recognition. Four in-the-wild datasets are evaluated: AFEW, SFEW, MELD and AffWild2. A multimodal architecture previously designed is used to perform the evaluation and classical metrics such as accuracy and F1-Score are used to measure performance in training and to validate quantitative results. However, strengths and weaknesses of these datasets for various uses indicate that by themselves they are not appropriate for multimodal recognition due to their original purpose, e.g., face or speech recognition. Therefore, we recommend a combination of multiple datasets in order to obtain better results when new samples are being processed and a good balance in the number of samples by class.

Anger, agency, risk and action: a neurobehavioral model with proof-of-concept in healthy young adults

Introduction

Anger can engender action by individuals and groups. It is thus important to understand anger's behavioral phenotypes and their underlying neural substrates. Here, we introduce a construct we term agentic anger, a negatively valenced internal state that motivates action to achieve risky goals. We evaluate our neurobehavioral model via testable hypotheses in two proof-of-concept studies.

Study 1 Methods

Study 1 used the Incentive Balloon Analogue Risk Task in a within-subjects, repeated measures design in 39 healthy volunteers to evaluate: (a) impact of blockade of reward on agentic anger, assessed by self-reports of negative activation (NA), (b) impact of achievement of reward on exuberance, assessed by self-reports of positive activation (PA), (c) the interrelationship of these valenced states, and (d) their relationship with personality.

Study 1 Results

Task-induced NA was positively correlated with task-induced PA, risk-taking on the task and trait Social Potency (SP), a measure of trait agency and reward sensitivity on the Multidimensional Personality Questionnaire Brief-Form.

Study 2 Methods

Study 2 assessed functional MRI response to stakes for risk-taking in healthy volunteers receiving 20 mg d-amphetamine in a double-blinded, placebo-controlled crossover design (N = 10 males), providing preliminary information on ventral striatal response to risky rewards during catecholamine activation.

Study 2 Results

Trait SP and task-induced PA were strongly positively related to catecholamine-facilitated BOLD response in the right nucleus accumbens, a brain region where DA prediction error signal shapes action value and selection. Participants' task-induced NA was strongly positively related with trait SP and task-induced PA, replicating the findings of Study 1.

Discussion

Together these results inform the phenomenology and neurobiology of agentic anger, which recruits incentive motivational circuitry and motivates personal action in response to goals that entail risk (defined as exposure to uncertainty, obstacles, potential harm, loss and/or financial, emotional, bodily, or moral peril). Neural mechanisms of agency, anger, exuberance, and risk-taking are discussed, with implications for personal and group action, decision-making, social justice, and behavior change.

Emotions as social information in unambiguous situations: role of emotions on procedural justice perception

Emotion as Social Information Theory claims that in an ambiguous situation, people rely on others' emotions to make sense of the level of fairness encountered. We tested whether the information provided by emotions about the fairness of a procedure is still a significant factor in explaining individual differences in perception of variance, even in unambiguous situations. We assessed the effects of others' emotions on observers inferred procedural justice during (un)ambiguous situations when people are treated (un)fairly. We collected data using Qualtrics online survey software from 1012 employees across different industry services in the United States. The participants were assigned randomly to one of the 12 experimental conditions (fair, unfair, and unknown x happiness, anger, guilt, and neutral). The results indicated that emotions played a significant role in the psychology of justice judgments under the ambiguous situation, as predicted by the EASI, as well as under unambiguous conditions. The study revealed significant interactions between the procedure and emotion. These findings emphasized the importance of considering how others' emotions influence an observer's perception of justice. The theoretical and practical implications of these findings were also discussed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-023-04640-y.

Emotion detection of social data: APIs comparative study

The development of emotion detection technology has emerged as an efficient possibility in the corporate sector due to the nearly limitless uses of this new discipline, particularly with the unceasing propagation of social data. In recent years, the electronic marketplace has witnessed the establishment of various start-up businesses with an almost sole focus on building new commercial and open-source tools and APIs for emotion detection and recognition. Yet, these tools and APIs must be continuously reviewed and evaluated, and their performances should be reported and discussed. There is a lack of research to empirically compare current emotion detection technologies in terms of the results obtained from each model using the same textual dataset. Also, there is a lack of comparative studies that apply benchmark comparisons to social data. This study compares eight technologies: IBM Watson Natural Language Understanding, ParallelDots, Symanto - Ekman, Crystalfeel, Text to Emotion, Senpy, Textprobe, and Natural Language Processing Cloud. The comparison was undertaken using two different datasets. The emotions from the chosen datasets were then derived using the incorporated APIs. The performance of these APIs was assessed using the aggregated scores they delivered and the theoretically proven evaluation metrics such as the micro-average of accuracy, classification error, precision, recall, and f1-score. Lastly, the assessment of these APIs incorporating the evaluation measures is reported and discussed.

Textual emotion detection utilizing a transfer learning approach

Many attempts have been made to overcome the challenges of automating textual emotion detection using different traditional deep learning models such as LSTM, GRU, and BiLSTM. But the problem with these models is that they need large datasets, massive computing resources, and a lot of time to train. Also, they are prone to forgetting and cannot perform well when applied to small datasets. In this paper, we aim to demonstrate the capability of transfer learning techniques to capture the better contextual meaning of the text and as a result better detection of the emotion represented in the text, even without a large amount of data and training time. To do this, we conduct an experiment utilizing a pre-trained model called EmotionalBERT, which is based on bidirectional encoder representations from transformers (BERT), and we compare its performance to RNN-based models on two benchmark datasets, with a focus on the amount of training data and how it affects the models' performance.

The Power of Discourse: Associations between Trainers' Speech and the Responses of Socialized Wolves and Dogs to Training

In a previous study, we found that Positive Reinforcement Training reduced cortisol of wolves and dogs; however, this effect varied across trainer-animal dyads. Here we investigate whether and how the trainers' use of speech may contribute to this effect. Dogs' great interest in high-pitched, intense speech (also known as Dog Directed Speech) has already been reported, but whether and how wolves respond similarly/differently to voice characteristics has never been studied before. We analyzed 270 training sessions, conducted by five trainers, with nine mixed-breed dogs and nine wolves, all human-socialized. Through Generalized Linear Mixed Models, we analyzed the effects of (a) three speech categories (nice, neutral, reprehensive) and laugh; and (b) acoustic characteristics of trainers' voices on animals' responses (correct responses, latency, orientation, time at less than 1 m, non-training behaviors, tail position/movements, cortisol variation). In both subspecies, tail wagging occurred more often in sessions with longer durations of nice speech, and less often in sessions with reprehensive speech. For dogs, the duration of reprehensive speech within a session was also negatively related to correct responses. For wolves, retreat time was associated with more reprehensive speech, whereas duration of nice speech was positively associated with time spent within one meter from the trainer. In addition, most dog behavioral responses were associated with higher average intonations within sessions, while wolf responses were correlated with lower intonations within sessions. We did not find any effects of the variables considered on cortisol variation. Our study highlights the relevance of voice tone and speech in a training context on animals' performances and emotional reactions.

Expressions of moral disgust reflect both disgust and anger

ABSTRACTPeople often appear to conflate anger and disgust, seemingly using expressions of both emotions interchangeably in response to moral violations. Yet, anger and moral disgust differ in their antecedents and consequences. These empirical observations are associated with two broad theoretical perspectives: one describes expressions of moral disgust as metaphors for anger, whereas the other describes moral disgust as functionally distinct from anger. Both accounts have received empirical support from separate and seemingly inconsistent literatures. The present study seeks to resolve this inconsistency by focusing on the different ways moral emotions have been measured. We formalise three theoretical models of moral emotions: one in which expressions of disgust are purely associated with anger (but not physiological disgust), one in which disgust and anger are fully separated and have distinct functions, and an integrative model that accommodates both metaphorical use in language and distinctive function. We test these models on responses to moral violations (four studies; N = 1608). Our results suggest that moral disgust has distinct functions, but that expressions of moral disgust are sometimes used to convey moralistic anger. These findings have implications for the theoretical status and measurement of moral emotions.

Impact of partner phubbing on negative emotions: a daily diary study of mitigating factors

Interactions between romantic partners may be disturbed by a co-present mobile phone use when a partner ignores their interaction partner in favor of a smartphone. This common practice, called phubbing, promotes social rejection and exclusion, hence the partner who gets phubbed may report negative emotional experiences. However, these experiences may be buffered by a cognitive perception mechanism, when the partner’s behavior is still perceived as responsive (i.e., understanding or validating). Thus, we hypothesize that feeling understood or validated moderate the link between phubbing intensity and negative emotions. To test our hypotheses, we conducted a daily diary study over seven days, using a sample of N = 133 participants living with their partner. Multilevel modeling was applied, to examine between- and within-person processes. The findings indicate that perception of the partner as understanding and validating, despite the co-present mobile phone use, reduces the negative emotional experiences during phubbing, and the interaction effects indicate nuances between phubbing and understanding and validation by partner, which extend our theoretical comprehension and distinguish between the two as separate relationship-related constructs. Our research provides a unique insight into how mechanisms related to couple interactions may reduce negative experiences, a finding that may be useful in future interventions and couples' therapy.

Emotion word use patterns and eating disorder symptoms: Considering the circumplex model of affect and basic emotions theory

OBJECTIVE

No prior research has examined whether the types of emotion words individuals use to describe their affective experiences cluster along affective dimensions inherent within leading affect theories, or how such emotion word use maps onto eating disorder (ED) symptoms.

METHOD

To address these gaps, latent profile analysis was used to empirically-identify groups of young adults (N = 352) by how often they use emotion words characterized by the circumplex model of affect's valence-arousal dimensions and basic emotions theory's basic versus complex emotion word categorizations. Auxiliary analyses examined differences in groups' ED symptoms (binge eating, purging, restricting, excessive exercising, muscle building, body dissatisfaction, and cognitive restraint).

RESULTS

The 5-profile valence-arousal model and 4-profile basic-complex model were the best-fitting theoretically-supported solutions. Valence-arousal profiles with greater negative affect valence generally exhibited worse ED pathology than others, whereas profiles with greater positive affect valence produced inconsistent risk- and protective-factor relations with distinct ED symptoms. Basic-complex profiles characterized by frequent use of both basic and complex emotion words generally had the greatest ED severity, and profiles with greater basic emotion word use exhibited elevated binge eating.

DISCUSSION

Individual-differences in young adults' emotion word use patterns, versus sample-level averages only, warrant further consideration in ED prevention and research.

PUBLIC SIGNIFICANCE

The present findings suggest that young adults differ in the types of words they use to describe their emotional experiences, and that these unique emotion word use patterns are linked to distinct eating disorder symptoms. These sources of variation warrant further consideration in eating disorders prevention efforts and future research seeking to advance affect-based eating disorders theories.

Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection

Sentiment Analysis is probably one of the best-known area in text mining. However, in recent years, as big data rose in popularity more areas of text classification are being explored. Perhaps the next task to catch on is emotion detection, the task of identifying emotions. This is because emotions are the finer grained information which could be extracted from opinions. So besides writer sentiments, writer emotion is also a valuable data. Emotion detection can be done using text, facial expressions, verbal communications and brain waves; however, the focus of this review is on text-based sentiment analysis and emotion detection. The internet has provided an avenue for the public to express their opinions easily. These expressions not only contain positive or negative sentiments, it contains emotions as well. These emotions can help in social behaviour analysis, decision and policy makings for companies and the country. Emotion detection can further support other tasks such as opinion mining and early depression detection. This review provides a comprehensive analysis of the shift in recent trends from text sentiment analysis to emotion detection and the challenges in these tasks. We summarize some of the recent works in the last five years and look at the methods they used. We also look at the models of emotion classes that are generally referenced. The trend of text-based emotion detection has shifted from the early keyword-based comparisons to machine learning and deep learning algorithms that provide more flexibility to the task and better performance.

Addressing the challenges of remorse in the criminal justice system

Remorse in offenders appears in a number of criminal justice domains. It is a mitigating factor in sentencing, influences parole decision making, may be influential in offender rehabilitation, and may be valued in forensic mental health. However, evaluation of remorse presents challenges in relation to evidence for remorse and expectations about its performance. Nevertheless, remorse is embedded deeply in criminal justice. The consideration of remorse in relation to emotions of shame, guilt and regret may offer an approach for evaluating remorse in sentencing and for addressing remorse in offender rehabilitation. This approach to understanding and working with remorse requires further elaboration, development and testing.

Trait anger and negative interpretation bias in neutral face perception

Introduction

Anger is a basic emotion helping people to achieve goals by preparing the body for action and prompting others to change their behavior but is also associated with health issues and risks. Trait anger, the disposition to experience angry feelings, goes along with an attribution of hostile traits to others. Negative distortions in the interpretation of social information have also been observed in anxiety and depression. The present study examined the associations between components of anger and negative interpretation tendencies in the perception of ambiguous and neutral schematic faces controlling for anxiety, depressed mood, and other variables.

Methods

A sample of 150 young adults performed a computer-based perception of facial expressions task and completed the State-Trait Anger Expression Inventory (STAXI-2) along with other self-report measures and tests.

Results

Trait anger and anger expression correlated with the perception of negative affects in neutral but not in ambiguous faces. More specifically, trait anger was linked to the attribution of anger, sadness, and anxiety to neutral faces. Trait anger predicted perceived negative affects in neutral faces when adjusting for anxiety, depression, and state anger.

Discussion

For neutral schematic faces, the present data support an association between trait anger and negatively biased interpretation of facial expression, which is independent of anxiety and depressed mood. The negative interpretation of neutral schematic faces in trait angry individuals seems not only to comprise the attribution of anger but also of negative emotions signaling weakness. Neutral schematic facial expressions might be useful stimuli in the future study of anger-related interpretation biases.

Happiness feels light and sadness feels heavy: introducing valence-related bodily sensation maps of emotions

Bodily sensation mapping (BSM) is a recently developed self-report tool for the assessment of emotions in which people draw their sensations of activation in a body silhouette. Following the circumplex model of affect, activity and valence are the underling dimensions of every emotional experience. The aim of this study was to introduce the neglected valence dimension in BSM. We found that participants systematically report valence-related sensations of bodily lightness for positive emotions (happiness, love, pride), and sensations of bodily heaviness in response to negative emotions (e.g., anger, fear, sadness, depression) with specific body topography (Experiment 1). Further experiments showed that both computers (using a machine learning approach) and humans recognize emotions better when classification is based on the combined activity- and valence-related BSMs compared to either type of BSM alone (Experiments 2 and 3), suggesting that both types of bodily sensations reflect distinct parts of emotion knowledge. Importantly, participants found it clearer to indicate their bodily sensations induced by sadness and depression in terms of bodily weight than bodily activity (Experiment 2 and 4), suggesting that the added value of valence-related BSMs is particularly relevant for the assessment of emotions at the negative end of the valence spectrum.

Responses of the public towards the government in times of crisis

We experimentally investigate how and when the public responds to government actions during times of crisis. Public reactions are shown to follow different processes, depending on whether government performs in exemplary or unsatisfactory ways to the COVID-19 pandemic. The 'how' question is addressed by proposing that negative moral emotions mediate public reactions to bad government actions, and positive moral emotions mediate reactions to good government actions. Tests of mediation are conducted while taking into account attitudes and trust in the government as rival hypotheses. The 'when' question is studied by examining self-regulatory moderators governing the experience of moral emotions and their effects. These include conspiracy beliefs, political ideology, attachment coping styles and collective values. A total of 357 citizens of a representative sample of adult Norwegians were randomly assigned to two experimental groups and a control group, where complaining, putting pressure on the government and compliance to Covid-19 policies were dependent variables. The findings show that negative moral emotions mediate the effects of government doing badly on complaining and pressuring the government, with conspiracy beliefs moderating the experience of negative moral emotions and attachment coping moderating the effects of negative moral emotions. The results also show that positive moral emotions mediate the effects of government doing well on compliance with COVID-19 regulations, with political ideology moderating the experience of positive moral emotions and collective values moderating the effects of positive moral emotions.