Emotion Generation Process Research Articles

Emotion-driven reasoning model for agent-based human–computer negotiation

Human-computer negotiation plays an important role in today's highly developed online transactions. Agents need to have higher emotional intelligence to deal with the random actions of human adversaries. Most of the existing studies focus on deterministic modeling but neglect the role of fuzziness in human–computer negotiation and emotion effects on the interaction between persuasion strategy selection and issue updating. This paper uses emotional rendering to describe the emotional interaction between agents to supplement the emotion generation process in agent-based negotiation. Moreover, this paper constructs emotion-driven reasoning model which integrates an agent’s assessment of emotion and actual utility, and proposes a mechanism for the selection of persuasion strategies and negotiating issue updating driven by the agent’s reasoning ability. A series of agent-agent experiments are conducted, and a human–computer negotiation system is developed for the real human-agent experiment. The agent-agent experimental results show that, compared with the non-emotion model, the proposed model increases the joint utility by 55.1% and compared with the non-reasoning model, the proposed model improves the success rate by 49.2%. Meanwhile, the proposed model is superior to several existing competing models in terms of the success rate, the negotiating rounds, and the success utility. The human-agent experimental results show that the developed negotiation system can achieve satisfactory results with human opponents.

Research on the strategy of improving mental health well-being in universities based on game theory

Abstract In this paper, the participants' interaction input emotion is assessed to analyze the current student interaction relationship, and two influencing factors, friendliness and empathy, are extracted. Secondly, the psychological game process of interpersonal interaction is simulated to model the emotion generation process of participants and students, and the sub-game perfect equilibrium strategy of the embedded game is used as the optimal emotion selection strategy. Finally, the student’s emotional states are updated according to the optimal emotional strategy, and the spatial coordinates of students’ emotional states after being stimulated by emotions are labeled with the spatial coordinates of six basic emotions. The results show that the happiness enhancement strategy based on the game model increases from 0 to 0.9, and the effectiveness increases to 1.0.

Personality Enhanced Emotion Generation Modeling for Dialogue Systems

Emotion plays a crucial role in human communication, as it adds depth and richness to conversations. In recent years, there has been growing interest in developing conversation systems with the ability to generate emotions. However, to create more engaging and realistic interactions, it is essential to consider the influence of personality on emotion generation. This paper proposes a novel approach that combines personality modeling with emotion generation for conversation systems. By incorporating personality traits into the emotion generation process, we aim to create more personalized and contextually appropriate emotional responses. Drawing from BigFive model and emotion computation techniques, our model takes into account individual differences in personality to generate emotions that align with each user’s unique characteristics. Experiments show that combining emotion modeling with personality in a dialogue system helps improve the performance of emotion generation models. Additionally, it is also verified that our approach outperforms other baselines on several metrics.

Emotion regulation research in hospitality and tourism

Purpose This paper aims to develop a comprehensive model on intra- and interpersonal emotion regulation (ER) in hospitality and tourism (H&T) service encounters. Design/methodology/approach A critical review and reflection of ER research from multiple disciplines was conducted. Methodologies appropriate for investigating ER were also reviewed. Findings A comprehensive framework was proposed to outline key influential factors, processes and consequences of intra- and interpersonal ER in service encounters in the H&T industry. Methodologies integrating advanced tools were suggested to measure complex and dynamic emotion generation and regulation processes in social interactions from a multimodal perspective. Research limitations/implications The researchers developed a comprehensive conceptual model on both intra- and interpersonal ER based on a critical review of the most recent psychological research on ER. Various theoretical and methodological considerations are discussed, offering H&T scholars a solid starting point to explore dynamic emotion generation and regulation processes in complex social settings. Moreover, the model provides future directions for the expansion of ER theories, which have been mostly developed and tested based on laboratory research. Originality/value The proposed model addresses two critical issues identified in emotion research in the H&T field: the lack of a dynamic perspective and the neglect of the social nature of emotions. Moreover, the model provides a roadmap for future research.

The Process Model of Emotion Regulation Questionnaire: Assessing Individual Differences in Strategy Stage and Orientation.

The study of individual differences in emotion regulation has typically focused exclusively either on the stage of the emotion generation process at which regulation occurs or on the engagement versus disengagement orientation of the regulation efforts. We introduce a new measure that samples equally across each stage of the process model of emotion regulation and from both engagement and disengagement orientations. Through five studies (ntotal = 2,543), we present the development and convergent, discriminant, and predictive validity evidence for the Process Model of Emotion Regulation Questionnaire (PMERQ). We show the final 10-scale 45-item questionnaire has acceptable internal consistency, is invariant between genders and across the age range, and has sufficient convergent and discriminant validity. The PMERQ also predicts affective and relationship functioning with strategies occurring earlier in the process model generally showing the strongest effects. We propose the PMERQ is a valuable measure to assess individual differences in the use of emotion regulation strategies.

Recovering Individual Emotional States from Sparse Ratings Using Collaborative Filtering

A fundamental challenge in emotion research is measuring feeling states with high granularity and temporal precision without disrupting the emotion generation process. Here we introduce and validate a new approach in which responses are sparsely sampled and the missing data are recovered using a computational technique known as collaborative filtering (CF). This approach leverages structured covariation across individual experiences and is available in Neighbors, an open-source Python toolbox. We validate our approach across three different experimental contexts by recovering dense individual ratings using only a small subset of the original data. In dataset 1, participants (n=316) separately rated 112 emotional images on 6 different discrete emotions. In dataset 2, participants (n=203) watched 8 short emotionally engaging autobiographical stories while simultaneously providing moment-by-moment ratings of the intensity of their affective experience. In dataset 3, participants (n=60) with distinct social preferences made 76 decisions about how much money to return in a hidden multiplier trust game. Across all experimental contexts, CF was able to accurately recover missing data and importantly outperformed mean and multivariate imputation, particularly in contexts with greater individual variability. This approach will enable new avenues for affective science research by allowing researchers to acquire high dimensional ratings from emotional experiences with minimal disruption to the emotion-generation process.

Process-Oriented Measurement of Emotion Regulation: General and Specific Associations With Psychosocial Adjustment and Well-Being in (Pre-)Adolescence.

The development of emotion regulation (ER) is associated with children’s and adolescents’ psychosocial adjustment and well-being. In this regard, previous studies have examined the role of different ER strategies, which can be characterized as being functional (e.g., reappraisal, problem solving) or dysfunctional (e.g., suppression, rumination). Based on the process model of emotion regulation, the strategies can also be classified according to their temporal position within the emotion generative process, with five families of ER strategies being proposed: situation selection, situation modification, attentional deployment, cognitive change, and response modulation. This study aimed to examine the role of ER for adolescents’ psychosocial adjustment (internalizing and externalizing problems, prosocial behavior) and well-being. First, associations were investigated on a more general level by distinguishing between functional and dysfunctional ER. Second, relations were examined on a more specific level by additionally distinguishing between the five families of ER strategies as suggested in the process model of ER. Questionnaire self-reports of N = 1,727 German children and adolescents (55% girls) aged 9–18 years (M = 13.03, SD = 1.75) collected in schools were analyzed. Path analyses showed that more functional and less dysfunctional ER in general is associated with fewer internalizing and externalizing symptoms, and higher well-being. Prosocial behavior was only positively related to functional but not dysfunctional ER. Analyses of associations on the level of specific categories of ER strategies generally showed a similar pattern, but in part indicated differential associations with the dependent variables: Internalizing problems were particularly associated with functional situation selection, dysfunctional cognitive change, and dysfunctional response modulation. Externalizing problems were associated with functional situation selection and response modulation, as well as numerous dysfunctional strategies, none of which were particularly salient. Similarly, numerous rather than single specific associations emerged between prosocial behavior and the five categories of functional ER strategies. Well-being was particularly associated with functional situation selection and dysfunctional cognitive change. Overall, a more precise assessment of ER, as implemented in this study, could not only advance research in this field, but can also be helpful in planning and evaluating prevention and intervention programs.

Optimism, Daily Stressors, and Emotional Well-Being Over Two Decades in a Cohort of Aging Men.

Growing evidence supports optimism as a health asset, yet how optimism influences well-being and health remains uncertain. We evaluated 1 potential pathway-the association of optimism with daily stress processes-and tested 2 hypotheses. The stressor exposure hypothesis posits that optimism would preserve emotional well-being by limiting exposure to daily stressors. The buffering hypothesis posits that higher optimism would be associated with lower emotional reactivity to daily stressors and more effective emotional recovery from them. Participants were 233 men from the Veterans Affairs Normative Aging Study who completed the Minnesota Multiphasic Personality Inventory-2 Revised Optimism-Pessimism scale in 1986/1991 and participated in up to three 8-day daily diary bursts in 2002-2010 (age at first burst: M = 76.7, SD = 6.5). Daily stressor occurrence, positive affect (PA), and negative affect (NA) were assessed nightly. We evaluated the hypotheses using multilevel structural equation models. Optimism was unrelated to emotional reactivity to or recovery from daily stressors. Higher optimism was associated with higher average daily PA (B = 2.31, 95% Bayesian credible interval [BCI]: 1.24, 3.38) but not NA, independent of stressor exposure. Lower stressor exposure mediated the association of higher optimism with lower daily NA (indirect effect: B = -0.27, 95% BCI: -0.50, -0.09), supporting the stressor exposure hypothesis. Findings from a sample of older men suggest that optimism may be associated with more favorable emotional well-being in later life through differences in stressor exposure rather than emotional stress response. Optimism may preserve emotional well-being among older adults by engaging emotion regulation strategies that occur relatively early in the emotion-generative process.

Cognitive Emotional Interaction Model of Robot Based on Reinforcement Learning

In order to enhance the cognitive emotional computing ability of robot, a cognitive emotional interaction model of robot based on reinforcement learning is proposed, which combines immediate feedback and long-term trend according to PAD(Pleasure-Arousal-Dominance) emotional space. Firstly, according to the psychology theory of interpersonal communication, the human emotion generation process is simulated to generate human-like emotions, and the three influencing factors of similarity, positivity and empathy are extracted. Secondly, the relationship between the response emotion+ state and the contexted long-term emotion state is established by using the global co-ordination feature of reinforcement learning, so as to model the robot emotion generation process. Then, three factors are incorporated into the model reward mechanism for the evaluate of the interactive emotion state, to update the model and get the optimal emotional strategy. Finally, the optimal emotional state corresponding to the obtained optimal emotional strategy is used to update the robot's emotional state transition probability, and based on the sentiment values of the six basic emotional states in space, them are mapped to continuous emotional space to get the optimal response emotional value of the robot. Subjective and objective comparison experiments show that the model in this paper can effectively increase the delicateness, continuity, positivity and empathy of the robot's emotional expression, and can effectively reduce the robot's dependence on external emotional stimuli, further improving the harmonious and friendly human-computer interaction.

Computational Emotion Models: A Thematic Review

Several computational models of emotions have been proposed to enable artificial agents to generate emotions of their own. However, there are barriers that limit the full capabilities of these models. One issue is the need to enable emotion generation in autonomous agents in wide range of interaction situations instead of designing specific scenarios. Additionally, it is not practically easy task to ‘effectively’ integrate other human characteristics in emotion generation process of artificial agents, which is essential for variation in behavioural responses of such agents. Moreover, although theoretically it is believed that appraisal variables are associated with emotion intensities, existing emotion literature does not offer a generalisable mechanism to computationally achieve such a mapping—thereby leading to ad-hoc implementations. It is also important to note that emotions expressed by intelligent autonomous agents like robots can have deep impact on people and society, therefore, it is crucial to ensure ethical implications of emotional responses of such systems. In this paper, we endeavour to review the emotion models proposed in the last two decades based on the aspects discussed above and provide recommendations for the development of future computational models of emotion. Our review will mainly revolve around the emotion models that implement the concept of appraisal theory of emotion. Our finding suggests that none of the existing computational models of emotion using appraisal theory implement all the characteristics we identify thereby providing further research opportunities.

Emotion regulation.

Emotion regulation (ER) refers to attempts to influence emotions in ourselves or others. Over the past several decades, ER has become a popular topic across many subdisciplines within psychology. One framework that has helped to organize work on ER is the process model of ER, which distinguishes 5 families of strategies defined by when they impact the emotion generation process. The process model embeds these ER strategies in stages in which a need for regulation is identified, a strategy is selected and implemented, and monitoring occurs to track success. Much of the research to date has focused on a strategy called cognitive reappraisal, which involves changing how one thinks about a situation to influence one's emotional response. Reappraisal is thought to be generally effective and adaptive, but there are important qualifications. In this article, we use reappraisal as an example to illustrate how we might consider 4 interrelated issues: (a) the consequences of using ER, either when instructed or spontaneous; (b) how ER success and frequency are shaped by individual and environmental determinants; (c) the psychological and neurobiological mechanisms that make ER possible; and (d) interventions that might improve how well and how often people use ER. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Trait neuroticism and emotion neurocircuitry: Functional magnetic resonance imaging evidence for a failure in emotion regulation.

Though theory suggests that individual differences in neuroticism (a tendency to experience negative emotions) would be associated with altered functioning of the amygdala (which has been linked with emotionality and emotion dysregulation in childhood, adolescence, and adulthood), results of functional neuroimaging studies have been contradictory and inconclusive. We aimed to clarify the relationship between neuroticism and three hypothesized neural markers derived from functional magnetic resonance imaging during negative emotion face processing: amygdala activation, amygdala habituation, and amygdala-prefrontal connectivity, each of which plays an important role in the experience and regulation of emotions. We used general linear models to examine the relationship between trait neuroticism and the hypothesized neural markers in a large sample of over 500 young adults. Although neuroticism was not significantly associated with magnitude of amygdala activation or amygdala habituation, it was associated with amygdala-ventromedial prefrontal cortex connectivity, which has been implicated in emotion regulation. Results suggest that trait neuroticism may represent a failure in top-down control and regulation of emotional reactions, rather than overactive emotion generation processes, per se. These findings suggest that neuroticism, which has been associated with increased rates of transdiagnostic psychopathology, may represent a failure in the inhibitory neurocircuitry associated with emotion regulation.

Difficulties with emotion regulation as a transdiagnostic mechanism linking child maltreatment with the emergence of psychopathology.

Childhood maltreatment is associated with increased risk for most forms of psychopathology. We examine emotion dysregulation as a transdiagnostic mechanism linking maltreatment with general psychopathology. A sample of 262 children and adolescents participated; 162 (61.8%) experienced abuse or exposure to domestic violence. We assessed four emotion regulation processes (cognitive reappraisal, attention bias to threat, expressive suppression, and rumination) and emotional reactivity. Psychopathology symptoms were assessed concurrently and at a 2-year longitudinal follow-up. A general psychopathology factor (p factor), representing co-occurrence of psychopathology symptoms across multiple internalizing and externalizing domains, was estimated using confirmatory factor analysis. Maltreatment was associated with heightened emotional reactivity and greater use of expressive suppression and rumination. The association of maltreatment with attention bias varied across development, with maltreated children exhibiting a bias toward threat and adolescents a bias away from threat. Greater emotional reactivity and engagement in rumination mediated the longitudinal association between maltreatment and increased general psychopathology over time. Emotion dysregulation following childhood maltreatment occurs at multiple stages of the emotion generation process, in some cases varies across development, and serves as a transdiagnostic mechanism linking child maltreatment with general psychopathology.

Systematic review and meta-analysis of age-related differences in instructed emotion regulation success.

The process model of emotion regulation (ER) is based on stages in the emotion generative process at which regulation may occur. This meta-analysis examines age-related differences in the subjective, behavioral, and physiological outcomes of instructed ER strategies that may be initiated after an emotional event has occurred; attentional deployment, cognitive change, and response modulation. Within-process strategy, stimulus type, and valence were also tested as potential moderators of the effect of age on ER. A systematic search of the literature identified 156 relevant comparisons from 11 studies. Few age-related differences were found. In our analysis of the subjective outcome of response modulation strategies, young adults used expressive enhancement successfully (g = 0.48), but not expressive suppression (g = 0.04). Response modulation strategies had a small positive effect among older adults, and enhancement vs suppression did not moderate this success (g = 0.31 and g = 0.10, respectively). Young adults effectively used response modulation to regulate subjective emotion in response to pictures (g = 0.41) but not films (g = 0.01). Older adults were able to regulate in response to both pictures (g = 0.26) and films (g = 0.11). Interestingly, both age groups effectively used detached reappraisal, but not positive reappraisal to regulate emotional behavior. We conclude that, in line with well-established theories of socioemotional aging, there is a lack of evidence for age differences in the effects of instructed ER strategies, with some moderators suggesting more consistent effectiveness for older compared to younger adults.

Borderline personality disorder affective instability: What you know impacts how you feel.

The current study examined the role of conceptual knowledge and language in affective instability (AI) associated with borderline personality disorder (BPD). Forty-six females meeting criteria for BPD and 51 nonclinical female control participants without BPD completed a measure of general vocabulary and a semantic similarities task that provided estimates of the degree to which participants weighted information about valence and arousal in their understanding of emotion language. Feelings of valence and arousal were assessed using the Self-Assessment Manikin in response to 62 emotionally evocative images, which was used to derive estimates of AI. BPD status was associated with valence and arousal AI at a bivariate level, but not after controlling for language variables (general vocabulary and semantic valence and arousal foci). Participants with stronger as opposed to weaker vocabularies exhibited less AI, and participants who emphasized arousal more in their conceptual representations of emotions exhibited less AI than those who emphasized it to a lesser degree. With the inclusion of language variables in a regression equation with BPD status predicting AI, semantic arousal focus, but not general vocabulary, was a significant predictor of AI. Consistent with psychological constructionist models of emotion that specify an active role of language throughout the emotion generation process, these findings suggest that language capacity (general vocabulary and the degree to which arousal influences understanding of emotion words) is an important determinant of the AI associated with BPD. (PsycINFO Database Record

Do generation and regulation of emotions interact? Examination of their relationships in young adults

Emotions can be generated in response to inherently emotional perceptual properties of a stimulus (‘bottom up’) and in response to cognitive interpretations of an event (‘top down’). Similarly, emotion regulation (ER) strategies may deploy bottom-up or top-down processes, however the specific nature of these processes remains unclear. In this study we sought to replicate and extend previous studies that have investigated the interaction between ER and emotion generation. Specifically, we examined the relationship between both methods of emotion generation and ER in a sample of 75 undergraduate students who completed self-report questionnaires and a behavioral task of ER. We attempted to extend previous research by testing whether the positive effect of cognitive reappraisal on top-down generated emotions was specific to reappraisal or true of multiple ER strategies. Overall there was a main effect of generation such that top-down generated emotion was better regulated by cognitive reappraisal, expressive suppression, and appraisal strategies. We also found a main effect of ER such that cognitive reappraisal was perceived as the most successful ER strategy. We argue that ER is a state-dependent process that includes dynamic cycles between emotion generation and regulation processes. We further discuss expressive suppression as a top-down emotion regulation strategy in the context of our study despite debated literature.

Emotion Malleability Beliefs Influence the Spontaneous Regulation of Social Anxiety

The current study examined how manipulating individuals’ beliefs about emotion’s malleability influences the choices they make in how they spontaneously regulate their anxiety during a stressful social situation. Participants were randomly assigned to receive either an experimental manipulation that emotions are malleable or that emotions are fixed then completed an impromptu, brief speech task designed to elicit anxiety. We predicted that participants in the malleable emotion condition, compared to those in the fixed condition, would engage in more cognitive reappraisal to change the unfolding of an emotion earlier in the emotion generative process; we predicted that participants in the fixed emotion condition would engage in more expressive suppression, a late stage regulation strategy. Consistent with these predictions, participants in the malleable condition reported spontaneously engaging in more cognitive reappraisal during the stressful speech task, although this greater use of reappraisal was not significantly associated with a decrease in negative affect. These results suggest that beliefs about emotion malleability can systematically influence subsequent emotion regulatory behavior.

Timing effects of antecedent- and response-focused emotion regulation strategies

Distraction and cognitive reappraisal influence the emotion-generative process at early stages and have been shown to effectively attenuate emotional responding. Inhibiting emotion-expressive behavior is thought to be less beneficial due to later implementation, but empirical results are mixed. Thus, the current study examined the temporal dynamics of these emotion regulation strategies at attenuating the late positive potential (LPP) while participants were shown unpleasant pictures. Results revealed that all strategies successfully reduced the LPP and self-reported negative affect. We confirmed that distraction attenuated the LPP earlier than cognitive reappraisal. Surprisingly, expressive suppression affected emotional responding as early as distraction. This suggests that suppression was used preventively and disrupted the emotion-generative process from the very beginning instead of targeting the emotional response itself. Thus, the obtained results point to the importance of considering the point in time when response-focused emotion regulation strategies are being implemented.

Emotional state transition model based on stimulus and personality characteristics

In order to use mathematical methods to study how cognitive reappraisal strategies affect the output state of emotions, Gross's cognitive reappraisal strategy is transformed into a quantitative parameter which is proposed to describe the general perception of emotional events on the basis of the emotion regulation. According to Gross's emotional regulation model, the Finite State Machine (FSM) model is used for describing the process of emotional state transition and the Likert 5 grading scale is introduced to study the level of an individual's reappraisal according to the participant's self-evaluation. The experimental results verify that the algorithm can effectively describe the relationship between the reappraisal strategy, emotional events and an emotiongenerative process. There are multiple dimensions of a human's emotional state. Thus, in the field of human-computer interaction, further research requires the development of a specific algorithm which can be implemented by a computer for the emotion regulation process.

Experiential Avoidance as an Emotion Regulatory Function: An Empirical Analysis of Experiential Avoidance in Relation to Behavioral Avoidance, Cognitive Reappraisal, and Response Suppression

The purpose of the present study was to empirically test the suggestion that experiential avoidance in an emotion regulation context is best understood as an emotion regulatory function of topographically distinct strategies. To do this we examined whether a measure of experiential avoidance could statistically account for the effects of emotion regulation strategies intervening at different points of the emotion-generative process as conceptualized by Gross' (1998) process model of emotion regulation. The strategies under examination were behavioral avoidance, cognitive reappraisal, and response suppression. The specific hypotheses to be tested were (1) that behavioral avoidance, cognitive reappraisal, and response suppression would statistically mediate the differences in measures of psychological well-being between a clinical and nonclinical sample, but that (2) these indirect effects would be reduced to nonsignificant levels when controlling for differences in experiential avoidance. The results provide clear support for the first hypothesis with regard to all the studied strategies. In contrast to the second hypothesis, the results showed the predicted outcome pattern only for the response-focused strategy “response suppression” and not for cognitive reappraisal or behavioral avoidance. The results are interpreted and discussed in relation to theories on experiential avoidance and emotion regulation.