Pleasure, Arousal, Dominance: Mehrabian and Russell revisited

Entrainment of rhythmic tonal sequences on neural oscillations and the impact on subjective emotion

Music possesses a remarkable capacity to evoke a broad spectrum of subjective responses and promote healing in humans, with rhythm playing a crucial role among its various elements. Rhythmic entrainment is considered as one of the fundamental mechanisms, yet its subsequent behavioral responses and quantitative relationship remain unclear. In the study presented here, we combined behavioral and electroencephalography experiments to explore the relationship between neural entrainment and emotional responses to rhythmic auditory stimuli, focusing on the emotional dimensions of valence, arousal, and dominance. Our findings reveal that while all sequences across 12 different presenting rates significantly entrain neural oscillations, sequences at different rates elicit distinct impacts on subjective emotional experience. The intensity of neural entrainment is associated with changes in emotional valence and dominance under specific frequency conditions. This insight addresses a gap in the existing literature regarding the dominance dimension and provides potential for developing more targeted and precise clinical interventions to enhance emotional well-being in the future.

Socially interactive industrial robots: a PAD model of flow for emotional co-regulation

This article presents the development of a socially interactive industrial robot. An Avatar is used to embody a cobot for collaborative industrial assembly tasks. The embodied covatar (cobot plus its avatar) is introduced to support Flow experiences through co-regulation, interactive emotion regulation guidance. A real-time continuous emotional modeling method and an aligned transparent behavioral model, BASSF (Boredom, Anxiety, Self-efficacy, Self-compassion, Flow) is developed. The BASSF model anticipates and co-regulates counterproductive emotional experiences of operators working under stress with cobots on tedious industrial tasks. The targeted Flow experience is represented in the three-dimensional Pleasure, Arousal, and Dominance (PAD) space. We present how, despite their noisy nature, PAD signals can be used to drive the BASSF model with its theory-based interventions. The empirical results and analysis provides empirical support for the theoretically defined model, and clearly points to the need for data pre-filtering and per-user calibration. The proposed post-processing method helps quantify the parameters needed to control the frequency of intervention of the agent; still leaving the experimenter with a run-time adjustable global control of its sensitivity. A controlled empirical study (Study 1, N = 20), tested the model's main theoretical assumptions about Flow, Dominance, Self-Efficacy, and boredom, to legitimate its implementation in this context. Participants worked on a task for an hour, assembling pieces in collaboration with the covatar. After the task, participants completed questionnaires on Flow, their affective experience, and Self-Efficacy, and they were interviewed to understand their emotions and regulation during the task. The results from Study 1 suggest that the Dominance dimension plays a vital role in task-related settings as it predicts the participants' Self-Efficacy and Flow. However, the relationship between Flow, pleasure, and arousal requires further investigation. Qualitative interview analysis revealed that participants regulated negative emotions, like boredom, also without support, but some strategies could negatively impact wellbeing and productivity, which aligns with theory. Additional results from a first evaluation of the overall system (Study 2, N = 12) align with these findings and provide support for the use of socially interactive industrial robots to support wellbeing, job satisfaction, and involvement, while reducing unproductive emotional experiences and their regulation.

Assessing Basic Emotion via Machine Learning: Comparative Analysis of Number of Basic Emotions and Algorithms

This paper explores the use of machine learning (ML) methods to identify "clusters" of basic emotions based on pleasure, arousal, and dominance (PAD). The data was obtained from the Dataset for Emotion Analysis using Physiological Signals (DEAP), data collected within the Building and Designing Assistive Technology (BDAT) Lab using the International Affective Picture System (IAPS), and the scores of PAD from the IAPS. The objective is to develop an algorithm that maps a PAD score to clusters that express emotions, e.g., sadness or happiness. The elbow method was used to determine the optimal number of clusters (4-8), and nine different ML algorithms were compared. Decision Trees, polynomial support vector machines (SVMs) and linear SVMs provided accurate results. The Decision Tree demonstrated efficiency, during both testing and validation, in identifying the same clusters when analyzing both the DEAP and IAPS datasets. The dataset included limited data for each emotion creating the possibility of overfitting. However, when evaluating the results relative to previous research, the results added to the understanding of the nuances of emotion self-reporting and modelling.

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.

Database of Expressionist, Impressionist, and Post-Impressionist paintings: Affective norms for 60 art pieces

Modern painters' art is not only different from canvas created earlier, but also shows high internal variability. Being aware of the conditions arising from art history, we used paintings from three art movements-Impressionism, Post-Impressionism, and Expressionism, to see if we are able to respond to claims made by art theorists by using methods specific to social sciences, and validate the paintings as stimuli which might evoke different emotional reaction based on the movement they were created in. We wanted to conduct an exploratory analysis comparing the mean assessment of valence, arousal, and dominance among the three art movements. A total of 60 different paintings were selected (20 for each art movement) showing figurative works and visible human figures. They were assessed on five different affective scales: valence, arousal, dominance, origin, and subjective significance with use of Self-Assessment Manikins. The results showed expected differences in affective reactions to Expressionist paintings compared with those of Impressionist and Post-Impressionist ones. Therefore, we provided the very first dataset of emotional stimuli with validated affective norms, categorised by the art movement that they were created in and ready to be used in future experimental studies.

Liking music with and without sadness: Testing the direct effect hypothesis of pleasurable negative emotion

Negative emotion evoked in listeners of music can produce intense pleasure, but we do not fully understand why. The present study addressed the question by asking participants (n = 50) to self-select a piece of sadness-evoking music that was loved. The key part of the study asked participants to imagine that the felt sadness could be removed. Overall participants reported performing the task successfully. They also indicated that the removal of the sadness reduced their liking of the music, and 82% of participants reported that the evoked sadness also adds to the enjoyment of the music. The study provided evidence for a "Direct effect hypothesis", which draws on the multicomponent model of emotion, where a component of the negative emotion is experienced as positive during music (and other aesthetic) experiences. Earlier evidence of a mediator, such as 'being moved', as the source of enjoyment was reinterpreted in light of the new findings. Instead, the present study applied a semantic overlap explanation, arguing that sadness primes emotions that share meaning with sadness, such as being-moved. The priming occurs if the overlap in meaning is sufficient. The degree of semantic overlap was defined empirically. The present study therefore suggests that mediator-based explanations need to be treated with caution both as a finding of the study, and because of analytic limitations in earlier research that are discussed in the paper.

GAUDIE: Development, validation, and exploration of a naturalistic German AUDItory Emotional database

Since thoroughly validated naturalistic affective German speech stimulus databases are rare, we present here a novel validated database of speech sequences assembled with the purpose of emotion induction. The database comprises 37 audio speech sequences with a total duration of 92 minutes for the induction of positive, neutral, and negative emotion: comedian shows intending to elicit humorous and amusing feelings, weather forecasts, and arguments between couples and relatives from movies or television series. Multiple continuous and discrete ratings are used to validate the database to capture the time course and variabilities of valence and arousal. We analyse and quantify how well the audio sequences fulfil quality criteria of differentiation, salience/strength, and generalizability across participants. Hence, we provide a validated speech database of naturalistic scenarios suitable to investigate emotion processing and its time course with German-speaking participants. Information on using the stimulus database for research purposes can be found at the OSF project repository GAUDIE: https://osf.io/xyr6j/ .

The Human Affectome

Over the last decades, theoretical perspectives in the interdisciplinary field of the affective sciences have proliferated rather than converged due to differing assumptions about what human affective phenomena are and how they work. These metaphysical and mechanistic assumptions, shaped by academic context and values, have dictated affective constructs and operationalizations. However, an assumption about the purpose of affective phenomena can guide us to a common set of metaphysical and mechanistic assumptions. In this capstone paper, we home in on a nested teleological principle for human affective phenomena in order to synthesize metaphysical and mechanistic assumptions. Under this framework, human affective phenomena can collectively be considered algorithms that either adjust based on the human comfort zone (affective concerns) or monitor those adaptive processes (affective features). This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope the Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research.

Quantitative methods for group bibliotherapy research: a pilot study

Background

Bibliotherapy is under-theorized and under-tested: Its purposes and implementations vary widely, and the idea that 'reading is good for you' is often more assumed than demonstrated. One obstacle to developing robust empirical and theoretical foundations for bibliotherapy is the absence of analytical methods capable of providing sensitive yet replicable insights into complex textual material. This pilot study offers a proof-of-concept for new quantitative methods including VAD (valence-arousal-dominance) modelling of emotional variance and doc2vec modelling of linguistic similarity.

Methods

VAD and doc2vec modelling were used on conjunction with qualitative coding to analyse transcripts of reading-group discussions plus the literary texts being discussed, from two reading groups each meeting weekly for six weeks (including 9 participants [5 researchers (3 authors, 2 collaborators), 4 others] in Group 1, and 8 participants [2 authors, 6 others] in Group 2).

Results

In-text-discussion similarity was inversely correlated with emotional volatility in the group discussions (arousal: r = -0.25; p = ns; dominance: r = 0.21; p = ns; valence: r = -0.28; p = ns). Enjoyment or otherwise of the texts was less significant than other factors in shaping the significance and potential benefits of participation. (Texts with unpleasant or disturbing content that strongly shaped subsequent discussions of these texts were still able to sponsor 'healthy' discussions of this content.).

Conclusions

Our methods and findings offer for the field of bibliotherapy research both new possibilities for hypotheses to test, and viable ways of testing them. In particular, the use of natural language processing methods and word norm data offer valuable complements to intuitive human judgement and self-report when assessing the impact of literary materials. We also share observations on facilitation protocols, interpretative practices, and how our group reading model differs from other trials of group reading for wellbeing.

Feasibility and effectiveness study of applying a hallucinogen harm reduction and integration model to a mindfulness thinking intervention using virtual reality: A randomized controlled trial

Objective

The purpose of this study was to investigate whether a virtual reality (VR) program designed and developed based on the hallucinogenic harm reduction and integration (PHRI) clinical model could be more effective in guiding positive thinking training, improving positive thinking awareness and ability, and, to some extent, facilitating personal efficacy and emotional state compared to a traditional VR program that places users in a virtual natural ecological environment to guide positive thinking training. We also sought to understand the factors that may influence the effectiveness of VR interventions and user experience.

Method

Seventy-six randomly recruited participants were divided into a control group and an experimental group of 38 participants, each according to a random number table, and were trained in VR meditation for eight weeks. The experimental group used a PHRI-based mindfulness program, while the control group used a traditional mindfulness meditation program. We used The Mindful Attention Awareness Scale and the PAD emotional three-dimensional scale to assess the level of state mindfulness and changes in the emotional state before and at the end of the experiment. The Immersive Tendencies Questionnaire measured the user's sense of presence and immersion in the virtual environment. The Five Facet Mindfulness Questionnaires and the Depression Anxiety and Stress Scale (DASS-21) were used at the baseline assessment stage before and at the 4-week follow-up after the experiment to assess the change in trait mindfulness levels due to the mindfulness training. The Five Facet Mindfulness Questionnaires and the DASS-21 were used to assess changes in mindfulness and mental health trait levels.

Results

At the end of the experiment, the MMSQ score was significantly lower in the control group than in the experimental group, while the ITQ score was significantly higher than in the experimental group, and both scores were statistically significant (p < 0.05). In the follow-up assessment four weeks after the end of the experiment, the FFMQ-15 score and the DASS-21 were significantly and statistically higher in the experimental group than in the control group (p < 0.05). Since the scores of the PAD scale did not obey a normal distribution, we used the Wilcoxon signed-rank test to assess the results, which proved that the experimental group had higher levels of emotional activation and arousal.

Conclusion

The VR positive thinking program developed based on PHRI can significantly increase the positive thinking state and emotional arousal and activation of the general population participants but does not directly lead to the growth of positive emotions. Moreover, this detached psychedelic scene brings users a weaker sense of presence and presence than traditional natural space scenes. Furthermore, it does not bring any intense simulator motion sickness symptoms. These findings suggest that VR programs developed based on PHRI have a more positive facilitation effect on the positive state and that this increase lasts longer than conventional VR-positive programs.

Problematic online anime (animation) use: It's relationship with viewers' satisfaction with life, emotions, and emotion regulation

Although there are numerous studies on problematic technology use, such as problematic video game use and problematic smartphone use, little is known about problematic online anime use. However, problematic online anime use warrants further examination because of anime's popularity and commercial importance. Furthermore, how emotion strategies and emotions (such as pleasure and arousal) invoked upon watching the online anime are associated with problematic online anime use is not examined in previous studies. To bridge these literature gaps and to contribute to the fields of emotion regulation and media psychology, this study adopts the emotion regulation theory and considers the relationships among viewers' satisfaction with life, feelings of pleasure and arousal arising from watching a particular online anime, cognitive emotion regulation strategies activated because of anime viewing, and potential to exhibit problematic behavior related to online anime use, which is operationalized as viewers' inability to control or reduce watching online anime. Data was collected from viewers who have watched the popular romantic comedy anime Kaguya-sama: Love Is War online via a major online discussion board in Taiwan through the purposive sampling method. Data analysis on the 190 online questionnaire returns (mostly from males and students) through the partial least squares analysis reveals that the emotion regulation theory can be used to examine viewers' perceptions of anime. In the online anime context, the emotion regulation strategy most likely to be invoked is positive refocusing (mean value of 3.68, measured through a 5-point Likert scale) which is in line with how people typically watch anime for immersion and escapism. Satisfaction with life demonstrates its robustness and flexibility in invoking the positive refocusing (path coefficient = 0.17) and refocus on planning (path coefficient = 0.13) strategies. It also lowers the adoption of the maladaptive strategy of catastrophizing (path coefficient = -0.18). While catastrophizing strategy (path coefficient = 0.31) and arousal (path coefficient = 0.24) add to problematic online anime use, pleasure (path coefficient = -0.27) lowers problematic online anime use. Thus, when viewers keep magnifying the severity of a bad situation they are in while watching online anime, instead of making them better, could lead them to the undesirable outcome of problematic online anime use. Although this study has provided several interesting insights, this study has only considered Kaguya-sama: Love Is War and used survey respondents' perception of their extent of problematic online anime use. To increase generalization, future studies could consider other types of anime and alternative means to measure problematic use, such as frequency of online anime viewing.

Unveiling the dynamics of emotions in society through an analysis of online social network conversations

Social networks can provide insights into the emotions expressed by a society. However, the dynamic nature of emotions presents a significant challenge for policymakers, politicians, and communication professionals who seek to understand and respond to changes in emotions over time. To address this challenge, this paper investigates the frequency, duration, and transition of 24 distinct emotions over a 2-year period, analyzing more than 5 million tweets. The study shows that emotions with lower valence but higher dominance and/or arousal are more prevalent in online social networks. Emotions with higher valence and arousal tend to last longer, while dominant emotions tend to have shorter durations. Emotions occupying the conversations predominantly inhibit others with similar valence and dominance, and higher arousal. Over a month, emotions with similar valences tend to prevail in online social network conversations.

ARAM: A Technology Acceptance Model to Ascertain the Behavioural Intention to Use Augmented Reality

The expansion of augmented reality across society, its availability in mobile platforms and the novelty character it embodies by appearing in a growing number of areas, have raised new questions related to people's predisposition to use this technology in their daily life. Acceptance models, which have been updated following technological breakthroughs and society changes, are known to be great tools for predicting the intention to use a new technological system. This paper proposes a new acceptance model aiming to ascertain the intention to use augmented reality technology in heritage sites-the Augmented Reality Acceptance Model (ARAM). ARAM relies on the use of the Unified Theory of Acceptance and Use of Technology model (UTAUT) model's constructs, namely performance expectancy, effort expectancy, social influence, and facilitating conditions, to which the new and adapted constructs of trust expectancy, technological innovation, computer anxiety and hedonic motivation are added. This model was validated with data gathered from 528 participants. Results confirm ARAM as a reliable tool to determine the acceptance of augmented reality technology for usage in cultural heritage sites. The direct impact of performance expectancy, facilitating conditions and hedonic motivation is validated as having a positive influence on behavioural intention. Trust expectancy and technological innovation are demonstrated to have a positive influence on performance expectancy whereas hedonic motivation is negatively influenced by effort expectancy and by computer anxiety. The research, thus, supports ARAM as a suitable model to ascertain the behavioural intention to use augmented reality in new areas of activity.

Emotion Recognition Using Different Sensors, Emotion Models, Methods and Datasets: A Comprehensive Review

In recent years, the rapid development of sensors and information technology has made it possible for machines to recognize and analyze human emotions. Emotion recognition is an important research direction in various fields. Human emotions have many manifestations. Therefore, emotion recognition can be realized by analyzing facial expressions, speech, behavior, or physiological signals. These signals are collected by different sensors. Correct recognition of human emotions can promote the development of affective computing. Most existing emotion recognition surveys only focus on a single sensor. Therefore, it is more important to compare different sensors or unimodality and multimodality. In this survey, we collect and review more than 200 papers on emotion recognition by literature research methods. We categorize these papers according to different innovations. These articles mainly focus on the methods and datasets used for emotion recognition with different sensors. This survey also provides application examples and developments in emotion recognition. Furthermore, this survey compares the advantages and disadvantages of different sensors for emotion recognition. The proposed survey can help researchers gain a better understanding of existing emotion recognition systems, thus facilitating the selection of suitable sensors, algorithms, and datasets.

Exploring the impact of functional, symbolic, and experiential image on approach behaviors among state-park tourists from India, Korea, and the USA

This study provides insights into the influence of state park image, visitor emotions, and place identity on visitors' revisit intentions by considering the moderating impact of national culture. A quantitative process with the data collected in India, Korea, and the US was used. Hierarchical regression analysis evidences the moderating role of national culture, which is hardly explored in the state park context. Results confirm that most hypotheses are fully or partially accepted, which suggests that brand image and national culture influence visitor intention. This study helps practitioners better understand the relevance of national culture in developing appropriate visitor attraction/retention strategies.

Does a three-dimensional Impact Message Inventory-Circumplex (IMI-C) enclose an indirect measure of reactance?

Clinicians can rely on the Impact Message Inventory-Circumplex (IMI-C) to map their emotional reactions to their patients' communication style in octant and main dimension scores on the two-dimensional interpersonal circle, based on affiliation (AFF) and control (CON) as the underlying main dimensions. However, modern emotion theories distinguish three, rather than two, robust dimensions of emotional experience and the perception of interpersonal behaviours: (1) positive versus negative evaluation (related to AFF), (2) strong versus weak (related to CON) and (3) active versus passive (arousal). In a large Dutch patient sample (N = 1,001), we first tested whether the two-dimensional circumplex structure of the IMI-C could be replicated using Browne's circumplex model. Then we explored whether a third dimension could be retrieved from therapists' IMI-C responses using exploratory factor analysis, followed by orthogonal target rotation towards a partially specified target matrix, with the first two factors specified according to the circumplex structure, and the other factor(s) left free. The two-dimensional circumplex of the IMI-C could be validated to a fair extent. Using exploratory factor models, we found supporting evidence for a third factor, which could be interpreted as reflecting reactance ('active' vs. 'passive' opposition). We recommend to extend the current two-dimensional interpretation to a three-dimensional interpretation of IMI-C responses, by adding a reactance dimension.

Assessing the association between subjective evaluation of space qualities and physiological responses through cinematic environments' emotion-eliciting stimuli

Objectives

Human perception of the built environment affects emotional and physiological states. This research focused on the association between evaluating a space's visual qualities and physiological responses by mediating film contents to indicate the association between physiological indicators and assessing the quality of space in the presence of environmental stimuli.

Method

Data collection was conducted using a psychological questionnaire and physiological indicators of heart rate (HR), blood pressure (BP), skin resistance level (SRL), and body temperature (BT) during the film screening. The ANOVA was conducted to compare different variables in the three films alongside linear regression to analyze the impact of variables on space quality. Spearman correlation coefficient analyses were performed to find the association between variables.

Results

The descriptive statistics showed significant changes in psychological and physiological variables in films. Associations between the NAQ factor and physiological changes in HR, SBP, and DBP factors were significant. The results derived from the simple and multiple linear regressions depicted the significant impact of physiological factors on HR and BP on perceiving the quality of space.

Conclusion

It was concluded that physiological changes caused by emotional arousal could be strongly associated with psychological assessments. Stimuli-affected video contents illustrating architectural spaces could efficiently extract the impact of physiological states and human cognitive responses to the space quality. Physiological characteristics related to the space appraisal could help realize the human-environment interaction in a multi-layered approach to the built environment and spatial cognition.

How multisensory perception promotes purchase intent in the context of clothing e-customisation

With the continuing development of internet technologies, an increasing number of consumers want to customise the products they buy online. In order to explore the relationship between perception and purchase intent, a conceptual framework was developed that was based on the link between multisensory perception, positive emotions, and purchase intent in fashion e-customisation marketing. We discuss the outcomes derived from consumers' experiences in fashion e-customisation and analyse the relationships between variables. Questionnaires were used to collect data for this quantitative study (n = 398 participants). The data was analysed using factor analysis, correlation analysis, and regression analysis. The findings contribute to the field of clothing e-customisation by identifying the effects of visual perception, haptic imagery, and auditory stimulation on arousal, and purchase intent. Visual perception and haptic imagery exerted a positive influence over dominance. We also identify the effects of arousal and dominance on purchase intent, and assess the mediating effects of these variables on visual perception, haptic mental imagery, and purchase intent. The results highlight how fashion e-customisation marketing strategies can be adopted by managers in order to increase positive emotions and how multisensory perception can potentially be used to influence consumers' purchase behaviour.

On Serendipitous Campus Meetings: A User Survey

With campuses opening up and stimulating interactions among different campus users more and more, we aim to identify the characteristics of successful meeting places (locations) on campus. These can help practitioners such as campus managers and directors to further optimize their campus to facilitate unplanned or serendipitous meetings between academic staff and companies. A survey on three Dutch campuses, including questions on both services and locations, was analyzed both spatially and statistically using principal component (PC) and regression analysis. Four PCs were found for services (Relax, Network, Proximity and Availability) and three PCs were found for locations (Aesthetics, Cleaned and Indoor Environment). Personal characteristics as explanatory variables were not significant or only had very small effect sizes, indicating that a campus' design does not need to be tailored to certain user groups but can be effective for all. The pattern of successful locations is discussed, including the variables in each PC. These PCs provide a framework for practitioners who want to improve their campus' design to further facilitate unplanned meetings, thus contributing to cooperation between campus users, hopefully leading to further innovation.

Gender biases in the training methods of affective computing: Redesign and validation of the Self-Assessment Manikin in measuring emotions via audiovisual clips

Audiovisual communication is greatly contributing to the emerging research field of affective computing. The use of audiovisual stimuli within immersive virtual reality environments is providing very intense emotional reactions, which provoke spontaneous physical and physiological changes that can be assimilated into real responses. In order to ensure high-quality recognition, the artificial intelligence (AI) system must be trained with adequate data sets, including not only those gathered by smart sensors but also the tags related to the elicited emotion. Currently, there are very few techniques available for the labeling of emotions. Among them, the Self-Assessment Manikin (SAM) devised by Lang is one of the most popular. This study shows experimentally that the graphic proposal for the original SAM labelling system, as devised by Lang, is not neutral to gender and contains gender biases in its design and representation. Therefore, a new graphic design has been proposed and tested according to the guidelines of expert judges. The results of the experiment show an overall improvement in the labeling of emotions in the pleasure-arousal-dominance (PAD) affective space, particularly, for women. This research proves the relevance of applying the gender perspective in the validation of tools used throughout the years.

The Effect of Interaction between Followers and Influencers on Intention to Follow Travel Recommendations from Influencers in Indonesia Based on Follower-Influencer Experience and Emotional Dimension

Social media has become a very commonplace way for many people to have social interactions. The role of social media has changed from what was originally only a way to bridge social interactions, to becoming a business tool in various industries, one of which is the tourism industry. The interaction between social media users can create new ways to increase public awareness of existing tourist objects. One way to achieve that goal is by utilizing social media influencers. This study aims to identify the factors that influence the intention of the followers to follow the travel recommendations given by the influencer. This study uses the theory of follower-influencer experience and the theory of emotional dimensions, as well as their effect on the level of commitment and intention to follow the recommendation. This research was conducted by distributing surveys through social media and we managed to obtain a total of 203 valid respondents. The results of the study were analyzed using structural equation modeling (SEM), which showed that information experience and homophily experience had a significant effect on pleasure, arousal, and dominance. Pleasure and dominance have a significant effect on commitment, and commitment has a significant effect on the intention to follow the recommendation.

Assessment of the Patient’s Emotional Response with the RobHand Rehabilitation Platform: A Case Series Study

Cerebrovascular accidents have physical, cognitive and emotional effects. During rehabilitation, the main focus is placed on motor recovery, yet the patient’s emotional state should also be considered. For this reason, validating robotic rehabilitation systems should not only focus on their effectiveness related to the physical recovery but also on the patient’s emotional response. A case series study has been conducted with five stroke patients to assess their emotional response towards therapies using RobHand, a robotic hand rehabilitation platform. Emotional state was evaluated in three dimensions (arousal, valence and dominance) using a computer-based Self-Assessment Manikin (SAM) test. It was verified that the emotions induced by the RobHand platform were successfully distributed in the three-dimensional emotional space. The increase in dominance and the decrease in arousal during sessions reflects that patients had become familiar with the rehabilitation platform, resulting in an increased feeling of control and finding the platform less attractive. The results also reflect that patients found a therapy based on a virtual environment with a realistic scenario more pleasant and attractive.

Fear Detection in Multimodal Affective Computing: Physiological Signals versus Catecholamine Concentration

Affective computing through physiological signals monitoring is currently a hot topic in the scientific literature, but also in the industry. Many wearable devices are being developed for health or wellness tracking during daily life or sports activity. Likewise, other applications are being proposed for the early detection of risk situations involving sexual or violent aggressions, with the identification of panic or fear emotions. The use of other sources of information, such as video or audio signals will make multimodal affective computing a more powerful tool for emotion classification, improving the detection capability. There are other biological elements that have not been explored yet and that could provide additional information to better disentangle negative emotions, such as fear or panic. Catecholamines are hormones produced by the adrenal glands, two small glands located above the kidneys. These hormones are released in the body in response to physical or emotional stress. The main catecholamines, namely adrenaline, noradrenaline and dopamine have been analysed, as well as four physiological variables: skin temperature, electrodermal activity, blood volume pulse (to calculate heart rate activity. i.e., beats per minute) and respiration rate. This work presents a comparison of the results provided by the analysis of physiological signals in reference to catecholamine, from an experimental task with 21 female volunteers receiving audiovisual stimuli through an immersive environment in virtual reality. Artificial intelligence algorithms for fear classification with physiological variables and plasma catecholamine concentration levels have been proposed and tested. The best results have been obtained with the features extracted from the physiological variables. Adding catecholamine’s maximum variation during the five minutes after the video clip visualization, as well as adding the five measurements (1-min interval) of these levels, are not providing better performance in the classifiers.

Five studies evaluating the impact on mental health and mood of recalling, reading, and discussing fiction

Does reading fiction improve mental health and well-being? We present the results of five studies that evaluated the impact of five forms of exposure to fiction. These included the effects of recalling reading fiction, of being prescribed fiction, of discussing fiction relative to non-fiction, and of discussing literary fiction relative to best-seller fiction. The first three studies directly recruited participants; the final two relied on scraped social media data from Reddit and Twitter. Results show that fiction can have a positive impact on measures of mood and emotion, but that a process of mnemonic or cognitive consolidation is required first: exposure to fiction does not, on its own, have an immediate impact on well-being.

Effects of Stores’ Environmental Components on Chinese Consumers’ Emotions and Intentions to Purchase Luxury Brands: Integrating Partial Least Squares-Structural Equation Modeling and Fuzzy-Set Qualitative Comparative Analysis Approaches

Purpose

Drawing upon the stimulus-organism-response (S-O-R) model, this paper aims to investigate the effects of stores’ environmental components (i.e., lighting, cleanliness, scent, design, layout, music, and employee interaction) on Chinese consumers’ emotions and intentions to purchase luxury brands.

Design/Methodology/Approach

Data were collected from Chinese consumers who have purchased luxury brands from retail stores. Partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were employed for data analysis.

Findings

The results of PLS-SEM indicated that three dimensions of the store environment (i.e., music, scent, and employee interaction) directly and significantly influenced Chinese consumers’ emotions. However, fsQCA revealed greater heterogeneity among respondents by highlighting stores’ environmental components and Chinese consumers’ emotions.

Originality/Value

This study makes significant contributions to the marketing literature by examining the S-O-R model alongside fsQCA approach to conditionally predict outcomes in a luxury brand context. The present study may be one of the first to examine the effects of stores’ environmental components on Chinese consumers’ emotions and purchase intentions, applying both symmetrical test (PLS-SEM) and asymmetrical test (fsQCA) approaches to determine significant components of the store environment as well as component combinations that predict Chinese consumers’ emotions and purchase intentions.

Gender Differences in Emotional Connotative Meaning of Words Measured by Osgood's Semantic Differential Techniques in Young Adults

Semantic differential techniques are a useful, well-validated tool to assess affective processing of stimuli and determine how that processing is impacted by various demographic factors, such as gender. In this paper, we explore differences in connotative word processing between men and women as measured by Osgood's semantic differential and what those differences imply about affective processing in the two genders. We recruited 94 young participants (47 men, 47 women, ages 18-39) using an online survey and collected their affective ratings of 120 words on three rating tasks: Evaluation (E), Potency (P), and Activity (A). With these data, we explored the theoretical and mathematical overlap between Osgood's affective meaning factor structure and other models of emotional processing commonly used in gender analyses. We then used Osgood's three-dimensional structure to assess gender-related differences in three affective classes of words (words with connotation that is Positive, Neutral, or Negative for each task) and found that there was no significant difference between the genders when rating Positive words and Neutral words on each of the three rating tasks. However, young women consistently rated Negative words more negatively than young men did on all three of the independent dimensions. This confirms the importance of taking gender effects into account when measuring emotional processing. Our results further indicate there may be differences between Osgood's structure and other models of affective processing that should be further explored.

Dynamic Tracking of State Anxiety via Multi-Modal Data and Machine Learning

Anxiety induction is widely used in the investigations of the mechanism and treatment of state anxiety. State anxiety is accompanied by immediate psychological and physiological responses. However, the existing state anxiety measurement, such as the commonly used state anxiety subscale of the State-Trait Anxiety Inventory, mainly relies on questionnaires with low temporal resolution. This study aims to develop a tracking model of state anxiety with high temporal resolution. To capture the dynamic changes of state anxiety levels, we induced the participants' state anxiety through exposure to aversive pictures or the risk of electric shocks and simultaneously recorded multi-modal data, including dimensional emotion ratings, electrocardiogram, and galvanic skin response. Using the paired self-reported state anxiety levels and multi-modal measures, we trained and validated machine learning models to predict state anxiety based on psychological and physiological features extracted from the multi-modal data. The prediction model achieved a high correlation between the predicted and self-reported state anxiety levels. This quantitative model provides fine-grained and sensitive measures of state anxiety levels for future affective brain-computer interaction and anxiety modulation studies.

Expressing Personality Through Non-verbal Behaviour in Real-Time Interaction

The attribution of traits plays an important role as a heuristic for how we interact with others. Many psychological models of personality are analytical in that they derive a classification from reported or hypothesised behaviour. In the work presented here, we follow the opposite approach: Our personality model generates behaviour that leads an observer to attribute personality characteristics to the actor. Concretely, the model controls all relevant aspects of non-verbal behaviour such as gaze, facial expression, gesture, and posture. The model, embodied in a virtual human, affords to realistically interact with participants in real-time. Conceptually, our model focuses on the two dimensions of extra/introversion and stability/neuroticism. In the model, personality parameters influence both, the internal affective state as well as the characteristic of the behaviour execution. Importantly, the parameters of the model are based on empirical findings in the behavioural sciences. To evaluate our model, we conducted two types of studies. Firstly, passive experiments where participants rated videos showing variants of behaviour driven by different personality parameter configurations. Secondly, presential experiments where participants interacted with the virtual human, playing rounds of the Rock-Paper-Scissors game. Our results show that the model is effective in conveying the impression of the personality of a virtual character to users. Embodying the model in an artificial social agent capable of real-time interactive behaviour is the only way to move from an analytical to a generative approach to understanding personality, and we believe that this methodology raises a host of novel research questions in the field of personality theory.

The Language of the Times: Using the COVID-19 Pandemic to Assess the Influence of News Affect on Online Mental Health-Related Search Behavior across the United States

Background

The digital era has ushered in an unprecedented volume of readily accessible information, including news coverage of current events. Research has shown that the sentiment of news articles can evoke emotional responses from readers on a daily basis with specific evidence for increased anxiety and depression in response to coverage of the recent COVID-19 pandemic. Given the primacy and relevance of such information exposure, its daily impact on the mental health of the general population within this modality warrants further nuanced investigation.

Objective

Using the COVID-19 pandemic as a subject-specific example, this work aimed to profile and examine associations between the dynamics of semantic affect in online local news headlines and same-day online mental health term search behavior over time across the United States.

Methods

Using COVID-19–related news headlines from a database of online news stories in conjunction with mental health–related online search data from Google Trends, this paper first explored the statistical and qualitative affective properties of state-specific COVID-19 news coverage across the United States from January 23, 2020, to October 22, 2020. The resultant operationalizations and findings from the joint application of dictionary-based sentiment analysis and the circumplex theory of affect informed the construction of subsequent hypothesis-driven mixed effects models. Daily state-specific counts of mental health search queries were regressed on circumplex-derived features of semantic affect, time, and state (as a random effect) to model the associations between the dynamics of news affect and search behavior throughout the pandemic. Search terms were also grouped into depression symptoms, anxiety symptoms, and nonspecific depression and anxiety symptoms to model the broad impact of news coverage on mental health.

Results

Exploratory efforts revealed patterns in day-to-day news headline affect variation across the first 9 months of the pandemic. In addition, circumplex mapping of the most frequently used words in state-specific headlines uncovered time-agnostic similarities and differences across the United States, including the ubiquitous use of negatively valenced and strongly arousing language. Subsequent mixed effects modeling implicated increased consistency in affective tone (Spin_VA β=–.207; P<.001) as predictive of increased depression-related search term activity, with emotional language patterns indicative of affective uncontrollability (Flux_A β=.221; P<.001) contributing generally to an increase in online mental health search term frequency.

Conclusions

This study demonstrated promise in applying the circumplex model of affect to written content and provided a practical example for how circumplex theory can be integrated with sentiment analysis techniques to interrogate mental health–related associations. The findings from pandemic-specific news headlines highlighted arousal, flux, and spin as potentially significant affect-based foci for further study. Future efforts may also benefit from more expansive sentiment analysis approaches to more broadly test the practical application and theoretical capabilities of the circumplex model of affect on text-based data.

Emoji for Food and Beverage Research: Pleasure, Arousal and Dominance Meanings and Appropriateness for Use

Emoji have been argued to have considerable potential for emotion research but are struggling with uptake in part because knowledge about their meaning is lacking. The present research included 24 emoji (14 facial, 10 non-facial) which were characterized using the PAD model (Pleasure-Arousal-Dominance) of human affect by 165 consumers in New Zealand and 861 consumers in the UK. The results from the two countries were remarkably similar and contributed further evidence that emoji are suitable for cross-cultural research. While significant differences between the emoji were established for each of the PAD dimensions, the mean scores differed most on the Pleasure dimension (positive to negative), then on the Arousal dimension (activated to deactivated), and lastly on the Dominance dimension (dominance to submissive). The research also directly measured the perceived appropriateness of the 24 emoji for use with foods and beverages. The emoji face savoring food, clapping hands and party popper were in the top-5 for the highest appropriateness in food and beverage context for both studies, as was a strong negative expression linked to rejection (Study 1: face vomiting; Study 2: nauseated face). On the other hand, zzz and oncoming fist were considered as the least appropriate to be used in a food and beverage context in both studies. Again, the results from the UK and NZ were in good agreement and identified similar groups of emoji as most and least suitable for food-related consumer research.

Learning of affective meaning: revealing effects of stimulus pairing and stimulus exposure

Charles E. Osgood's theory of affective meaning defines affect as interplay of three meaning dimensions - evaluation, potency, and activity - that represent the central constituents of our affective ecology. Based on a rigorous Brunswikian sampling procedure, we selected a representative set of stimuli that mirror this ecology. A germane informative analysis explicates and corroborates the sampling approach. We then report two experiments testing whether these dimensions of affective meaning can be learnt by means of stimulus pairing and stimulus exposure. Our findings yield evidence for (1) stimulus pairing effects on evaluation and activity, and (2) stimulus exposure effects on potency and activity. Overall, the findings reveal that stimulus pairing and stimulus exposure differentially influence the learning of dimensions of affective meaning. We discuss implications of this research for current emotion theories as well as its contribution to research in the cognition-emotion interface. Finally, we argue that the implementation of representative design by virtue of Brunswikian sampling promotes theory development and opens new research avenues for an original and creative science of cognition and emotion.

A review on sentiment analysis and emotion detection from text

Social networking platforms have become an essential means for communicating feelings to the entire world due to rapid expansion in the Internet era. Several people use textual content, pictures, audio, and video to express their feelings or viewpoints. Text communication via Web-based networking media, on the other hand, is somewhat overwhelming. Every second, a massive amount of unstructured data is generated on the Internet due to social media platforms. The data must be processed as rapidly as generated to comprehend human psychology, and it can be accomplished using sentiment analysis, which recognizes polarity in texts. It assesses whether the author has a negative, positive, or neutral attitude toward an item, administration, individual, or location. In some applications, sentiment analysis is insufficient and hence requires emotion detection, which determines an individual's emotional/mental state precisely. This review paper provides understanding into levels of sentiment analysis, various emotion models, and the process of sentiment analysis and emotion detection from text. Finally, this paper discusses the challenges faced during sentiment and emotion analysis.

How Does Channel Integration Affect Consumers’ Selection of Omni-Channel Shopping Methods? An Empirical Study of U.S. Consumers

In recent years, fashion brands and retailers have been advancing rapidly to provide U.S. consumers more seamless omni-channel shopping experiences. The pandemic has further accelerated the growth of omni-channel shopping. This study aimed to explore the effects of channel integration in six aspects (i.e., promotion, product and price, transaction information, information access, order fulfillment, and customer service) on the U.S. consumers’ intentions to use three omni-channel shopping methods: buy online pick-up in-store (BOPI), buy online curbside pickup (BOCP), and buy in-store home delivery (BIHD). We proposed a mediation model to test the effects through consumer perceived values (hedonic value, utilitarian value), perceived risk, and perceived behavioral control. Furthermore, this study explored the moderating effect of perceived COVID-19 vulnerability on the relationships between consumers’ internal evaluations of channel integration and their shopping method selection intentions. A total of 516 eligible responses were gathered through a survey of U.S. consumers. Multiple regressions were applied to test the hypotheses. Six types of channel integration showed significant effects on the U.S. consumers’ internal evaluations, which in turn influence their intentions to use certain types of omni-channel shopping methods. Overall, the proposed model exhibits a satisfactory explanatory power.

The importance of servicescapes in Maldivian higher education: application of the stimuli-organism-response(SOR) framework

Purpose

This study aims to use the servicescape model of higher education environments to measure the students’ perceptions of the learning environment (classroom) and the effect this has on students’ learning ability.

Design/methodology/approach

The present study follows the stimulus-organism-response paradigm framework. A self-administered and well-structured survey questionnaire is used to collect data. The snowball sampling technique is used to collect samples of 403 students belonging to Maldivian higher education institutions.

Findings

Findings show that the physical appearances of these higher education institutions greatly influenced the pleasure dimension. Furthermore, pleasure is found to have a significant and positive relationship with the approach behaviour and engagement/involvement of the students.

Originality/value

The main contribution of the study is that it successfully tests the “Eduscape” model adopted from the servicescape model, and thus helps to extend existing knowledge on the critical elements in the Maldivian higher education learning environments and student’s behaviour within them. The findings have implications for higher education institutions to improve their learning environments and better engage with their students.

Effects of the new COVID-19 normal on customer satisfaction: Can facemasks level off the playing field between average-looking and attractive-looking employees?

The attractiveness of service employees can have a significant impact on customer attitudes and behaviors. While frontline employees can reduce the risk of the COVID-19 transmission and infection by wearing facemasks, doing so can also influence customers' perceptions of employees' attractiveness and thus affect customer satisfaction. Based on the Gestalt theory, this study explores the impact of hotel employees' facemask-wearing on customer satisfaction through two experimental studies. The results indicate that average-looking frontline employees who wear facemasks induce high levels of customer satisfaction. However, while the impact of wearing facemasks on customer satisfaction is not significant for attractive-looking male frontline employees, attractive-looking female frontline employees who wear facemasks induce lower customer satisfaction. Customers' perception of employees' physical attractiveness fully mediates the effects of wearing facemasks on customer satisfaction in the case of average-looking employees. Customers' self-perceived physical attractiveness moderates the mediated effects. Implications that can help hotel managers improve customers' service evaluations during the COVID-19 pandemic are provided.

The Role of Vocal Affect in Persuasion: The CIVA Model

Past research has largely focused on how emotional expressions provide information about the speaker’s emotional state, but has generally neglected vocal affect’s influence over communication effectiveness. This is surprising given that other nonverbal behaviors often influence communication between individuals. In the present theory paper, we develop a novel perspective called the Contextual Influences of Vocal Affect (CIVA) model to predict and explain the psychological processes by which vocal affect may influence communication through three broad categories of process: emotion origin/construal, changing emotions, and communication source inferences. We describe research that explores potential moderators (e.g., affective/cognitive message types, message intensity), and mechanisms (e.g., emotional assimilation, attributions, surprise) shaping the effects of vocally expressed emotions on communication. We discuss when and why emotions expressed through the voice can influence the effectiveness of communication. CIVA advances theoretical and applied psychology by providing a clear theoretical account of vocal affect’s diverse impacts on communication.

Aromachology and Customer Behavior in Retail Stores: A Systematic Review

Interest in the use of scents in retail environments for creating better customer experiences is growing. Yet, knowledge of the effectiveness of aromachology to affect actual customer behavior and ultimately increase turnover is incomplete, as published results present inconsistencies and are often based on highly controlled environments rather than actual store environments. Situated within this context, this paper offers a systematic review on research in aromachology with a focus on effects on actual customer behavior in actual retail environments. As expected, the available research on actual environments (relative to laboratory-based studies) is limited, with only 20 articles meeting the inclusion criteria. While reported results are, overall, indicative of the positive effects of scent on customers’ emotional states and on their in-store behavior (dwell time, product choices) and attitudes (purchase intention, intention to revisit), several critical issues with the available literature emerged. These pertain primarily to a lack of sufficient methodological details (specifically on the scents, their compositions, intensity and methods of delivery), a narrow focus on scents without considering interactions with other atmospherics factors, and a general disregard of individual differences in olfaction. The review provides suggestions for addressing these shortcomings and improving the quality and actionability of this line of research.

A Review on Speech Emotion Recognition Using Deep Learning and Attention Mechanism

Emotions are an integral part of human interactions and are significant factors in determining user satisfaction or customer opinion. speech emotion recognition (SER) modules also play an important role in the development of human–computer interaction (HCI) applications. A tremendous number of SER systems have been developed over the last decades. Attention-based deep neural networks (DNNs) have been shown as suitable tools for mining information that is unevenly time distributed in multimedia content. The attention mechanism has been recently incorporated in DNN architectures to emphasise also emotional salient information. This paper provides a review of the recent development in SER and also examines the impact of various attention mechanisms on SER performance. Overall comparison of the system accuracies is performed on a widely used IEMOCAP benchmark database.

Embodied power: Specific facial muscles automatically respond to power-related information processing

Derived from embodiment approaches, we tested the assumption that specific facial muscle contractions are simulated upon the categorization of power-related words. For this, we used an interference task that required participants to categorize trait adjectives according to their underlying power. Response latencies of contractions of either the corrugator supercilii (pulls the eyebrows together) or the depressor anguli oris muscle (pulls the corners of the mouth downwards) were assessed. In two experiments, we expected and found that the speed of facial responses crucially depends on whether a high power or low power adjective was categorized. More precisely, corrugator responses were faster to high power adjectives whereas depressor responses were faster to low power adjectives. These findings support the assumption that the meaning of power is at least partially grounded in motor representations underlying specific facial expressions.

Canabal M, Gutiérrez-Martín L, Lanza-Gutierrez JM, Portela-García M, López-Ongil C. Fear Recognition for Women Using a Reduced Set of Physiological Signals

Emotion recognition is benefitting from the latest research into physiological monitoring and wireless communications, among other remarkable achievements. These technologies can indeed provide solutions to protect vulnerable people in scenarios such as personal assaults, the abuse of children or the elderly, gender violence or sexual aggression. Cyberphysical systems using smart sensors, artificial intelligence and wearable and inconspicuous devices can serve as bodyguards to detect these risky situations (through fear-related emotion detection) and automatically trigger a protection protocol. As expected, these systems should be trained and customized for each user to ensure the best possible performance, which undoubtedly requires a gender perspective. This paper presents a specialized fear recognition system for women based on a reduced set of physiological signals. The architecture proposed is characterized by the usage of three physiological sensors, lightweight binary classification and the conjunction of linear (temporal and frequency) and non-linear features. Moreover, a binary fear mapping strategy between dimensional and discrete emotional information based on emotional self-report data is implemented to avoid emotional bias. The architecture is evaluated using a public multi-modal physiological dataset with two approaches (subject-dependent and subject-independent models) focusing on the female participants. As a result, the proposal outperforms the state-of-the-art in fear recognition, achieving a recognition rate of up to 96.33% for the subject-dependent model.

The Impact of Environmental Stimuli on Hotel Service Employees’ Service Sabotage—Mediation Role of Emotional Intelligence and Emotional Dissonance

While scholarly inquiries into Service Sabotage (SS) have received ample attention in the literature of various industries, the role of Emotional Intelligence (EI) and Emotional Dissonance (ED) in employee-customer relations in the context of Environmental Stimuli (ES) in the tourism accommodation sector has remained unexplored. The role of employee–customer interaction in tourism is paramount for a hospitality organization’s growth, sustainability, and profitability. We hypothesized hotel service employees’ EI and ED can be influential factors to SS. Adopting the Mehrabian–Russell model (M–R) and Stimulus-Organism-Response (S-O-R) framework as conceptual paradigms, we tested the effect of hotel ambiance on employees’ emotions, which can have significant effects on SS. The study revealed that ES links to behaviors and elicits EI and ED as human emotional responses to environments that have a parallel mediating effect on mitigating or neutralizing the negative effect of SS in an organization. The findings provide important insights into an organization’s awareness of the provision of ES as a positive factor for employees, subsequently forming their behavioral consequences of EI and ED which can mitigate the negative impacts of SS. The study yields important implications on how hospitality organizations should pay attention to the impact of rule-breaking behaviors. Theoretical and practical implications are also discussed.

Words describing feelings about death: A comparison of sentiment for self and others and changes over time

Understanding public attitudes towards death is needed to inform health policies to foster community death awareness and preparedness. Linguistic sentiment analysis of how people describe their feelings about death can add to knowledge gained from traditional self-reports. This study provided the first description of emotive attitudes expressed towards death utilising textual sentiment analysis for the dimensions of valence, arousal and dominance. A linguistic lexicon of sentiment norms was applied to activities conducted in an online course for the general-public designed to generate discussion about death. We analysed the sentiment of words people chose to describe feelings about death, for themselves, for perceptions of the feelings of ‘others’, and for longitudinal changes over the time-period of exposure to a course about death (n = 1491). The results demonstrated that sadness pervades affective responses to death, and that inevitability, peace, and fear were also frequent reactions. However, words chosen to represent perceptions of others’ feelings towards death suggested that participants perceived others as feeling more negative about death than they do themselves. Analysis of valence, arousal and dominance dimensions of sentiment pre-to-post course participation demonstrated that participants chose significantly happier (more positive) valence words, less arousing (calmer) words, and more dominant (in-control) words to express their feelings about death by the course end. This suggests that the course may have been helpful in participants becoming more emotionally accepting in their feelings and attitude towards death. Furthermore, the change over time appeared greater for younger participants, who showed more increase in the dominance (power/control) and pleasantness (valence) in words chosen at course completion. Sentiment analysis of words to describe death usefully extended our understanding of community death attitudes and emotions. Future application of sentiment analysis to other related areas of health policy interest such as attitudes towards Advance Care Planning and palliative care may prove fruitful.

Could L2 Lexical Attrition Be Predicted in the Dimension of Valence, Arousal, and Dominance?

The current study attended to predict L2 lexical attrition by means of a Decision Tree model (DT model) in three emotional dimensions, that is, the valence dimension, the arousal dimension, and the dominance dimension. A sample of 188 participants whose L1 was Chinese and L2 was English performed a recognition test of 500 words for measuring the L2 lexical attrition. The findings explored by the Decision Tree model indicated that L2 lexical attrition could be predicted in all the three emotional dimensions in two aspects: (1) among the three emotional dimensions, the valence dimension was the most powerful in predicting L2 lexical attrition, followed successively by the dominance dimension and the arousal dimension; (2) most of the neutral words in the three emotional dimensions were predicted to be inferior to emotional words in L2 attrition. In addition, the modified Revised Hierarchical Model for emotion could be adopted to justify the modulation of the emotion–memory effects upon L2 lexical attrition.

The impact of emotions on shopping behavior during epidemic. What a business can do to protect customers

The study investigated how the perception of in-shop COVID-19 contraction influences emotions in decision-making and how they further effect actions undertaken by consumers to control the situation within a store. Structural equation modeling was used to study the relationship between the risk of in-store infection, emotions and in-shop behavior, based on data retrieved from 914 questionnaires. Results showed, that the perceived risk of becoming infected in a store causes an increase in arousal and, at the same time, a decrease in perceived pleasure during shopping. The rise in arousal led to an increase in consumers taking actions to decrease their risk of contagion, while an increase in noticeable pleasure lowered interest of following recommendations for pandemic behavior. The findings imply that through changes regarding in-store atmosphere, stationary shops can provide consumers with a sense of urgency and awareness of infection risk so that they may do their shopping more efficiently.

A Minimal Setup for Spontaneous Smile Quantification Applicable for Valence Detection

Tracking emotional responses as they unfold has been one of the hallmarks of applied neuroscience and related disciplines, but recent studies suggest that automatic tracking of facial expressions have low validation. In this study, we focused on the direct measurement of facial muscles involved in expressions such as smiling. We used single-channel surface electromyography (sEMG) to evaluate the muscular activity from the Zygomaticus Major face muscle while participants watched music videos. Participants were then tasked with rating each video with regard to their thoughts and responses to each of them, including their judgment of emotional tone ("Valence"), personal preference ("Liking") and rating of whether the video displayed strength and impression ("Dominance"). Using a minimal recording setup, we employed three ways to characterize muscular activity associated with spontaneous smiles. The total time spent smiling (ZygoNum), the average duration of smiles (ZygoLen), and instances of high valence (ZygoTrace). Our results demonstrate that Valence was the emotional dimension that was most related to the Zygomaticus activity. Here, the ZygoNum had higher discriminatory power than ZygoLen for Valence quantification. An additional investigation using fractal properties of sEMG time series confirmed previous studies of the Facial Action Coding System (FACS) documenting a smoother contraction of facial muscles for enjoyment smiles. Further analysis using ZygoTrace responses over time to the video events discerned "high valence" stimuli with a 76% accuracy. Additional validation of this approach came against previous findings on valence detection using features derived from a single channel EEG setup. We discuss these results in light of both the recent replication problems of facial expression measures, and in relation to the need for methods to reliably assess emotional responses in more challenging conditions, such as Virtual Reality, in which facial expressions are often covered by the equipment used.