Emotional Preferences Research Articles

Colour Preference and Healing in Digital Roaming Landscape: A Case Study of Mental Subhealth Populations.

From the perspective of emotional preference, studies have been conducted about landscape healing for subhealth people in the National High-Tech Zone (the study area). Combined with a preliminary practice investigation, Unity 2019 was used to make a digital roaming landscape, and 91 subjects with a history of mental subhealth diseases were randomly invited to participate in the immersive experimentation of the Human–Machine Environment Synchronisation (ErgoLAB) platform. After the experiment, the subjects were invited to fill in a Likert scale as the control group. The interest preference, emotion fluctuation, and healing effect of landscape colour were verified. The results show that: (1) The variation trend of interest reflected the concentration of interest in landscape, and the order of degree of interest, ranging from high to low, went Green > Yellow > Blue > Red > Orange > Purple > Cyan. (2) The subjects’ interest in landscape colour was correlated with the arousal of positive emotions. The correlation between interest in landscape colour and positive emotions, from high to low, went Blue > Green > Yellow, while the correlation between red, cyan, orange, and purple was not significant. (3) The mean skin conductance (SC) fluctuation variance of subjects was 5.594%, which confirmed that the healing effect of digital roaming landscape scenes was significant under the state of low arousal. According to the Likert scale data, subjects’ scores of the healing effect of landscapes, from high to low, went as follows: Green > Yellow > Red > Blue > Cyan > Orange > Purple. The results provide a new method for demonstrating the logical relationship between the digital landscape interest experience–emotional awakening–healing effect and providing a theoretical method and construction scheme for landscape colour configuration in the implementation of landscape healing projects.

Rational and irrational factors that predict the continued intention to engage in digital reading: a perspective from China

Few studies have examined factors, including irrational factors, that affect the continued intention of digital reading. This research attempts to propose an integrated framework to understand the continued intention to engage in digital reading. Based on weighted and calculated needs for new media and the technology acceptance model, the current research empirically investigated continued digital reading using an online survey. The research examined two rational factors—technology characteristics (perceived ease of use, perceived usefulness, and relative advantage) and individual motivations (perceived needs and perceived value)—as well as two irrational factors (emotional preference and perceived herd behaviour).This study found that the perceived ease of use and relative advantage of digital reading, as well as users’ perceived needs (information needs and social needs), perceived value (perceived benefits), and the irrational factor of perceived herd behaviour could predict the continued intention to read digitally. We provided a theoretical framework for understanding the mechanisms of the continued intention to engage in digital reading. The research provided theoretical and practical enlightenment for the development and promotion of digital reading.

Using Kansei Engineering for the Design Thinking Framework: Bamboo Pen Holder Product Design

Recently, as a potential source of stationery products, bamboo has been continuously excavated for its commercial value in sustainable development. The research on the design of the bamboo pen holder, based on the concept of sustainable design, is not only a symbol of Chinese culture but also a reflection of perceptual factors underlying college students’ preferences. This study aims at user-centered product design by integrating Design Thinking (DT) and Kansei Engineering (KE). We proposed the KE–DT framework which allows designers to coordinate the user’s feelings as design elements. With various college student questionnaires, expert interviews, and cluster analysis, 7 Kansei words were selected to describe the sentimental value first. Using statistical analysis, the users’ emotional preference for each Kansei word was determined. Finally, the best shape of the pen holder was obtained by Sequential Quadratic Programming (SQP), and the stereoscopic product was displayed. A new round of questionnaire surveys was conducted with the optimized pen container and the previous group. The results indicated that curvature had a significant effect on the preference for bamboo stationery in terms of user and designer cognitive differences. Furthermore, the bamboo pen holder designed by the KE–DT framework proved widely popular.

An emotion role mining approach based on multiview ensemble learning in social networks

Emotion is a status that combines people’s feelings, thoughts, and behaviors, and plays a crucial role in communication among people. Large studies suggest that human emotions can also be conveyed through online interactions. Previous studies have addressed the mechanism of emotional contagion; however, emotional contagion, through users of online social networks, has not yet been thoroughly researched. Therefore, in this study, initially, the definition of emotion roles, which may play an important role in emotional contagion, is introduced. On this basis, an emotion role mining approach based on multiview ensemble learning (ERM-ME) is proposed to detect emotion roles in social networks by fusing the information contained in different features. The ERM-ME approach includes three stages: detection of emotional communities, local fusion, and global fusion. First, ERM-ME divides emotional communities based on user emotional preferences. Then, emotional features are employed to train basic classifiers, which are then combined into meta-classifiers. Finally, an accuracy-based weighted voting scheme is used to integrate the results of meta-classifiers to achieve a more accurate and comprehensive classification. Experiments and evaluations are performed using Flickr and Microblog datasets to verify the practicability and effectiveness of the proposed method. Extensive experimental results show that the proposed approach outperforms alternative methods. The micro F-score is used as an evaluation indicator. Using the ERM-ME approach, the indicator is improved by approximately 1.09%–14.57% on Flickr and 5.19%–8.95% on Microblog, compared with Graph Convolutional Network, random forest, AdaBoost, bagging, and stacking.

Emotional Intelligence and Individual Visual Preferences: A Predictive Machine Learning Approach

Differences in individuals’ psychological and cognitive characteristics have been always found to play a significant role in influencing our behavior and preferences. While a number of studies have identified the impact of these characteristics on individuals’ visual design preferences, understanding how emotional intelligence (EI) would influence this process is yet to be explored. This study investigated the link between individuals’ EI dimensions (eg, emotionality, self-control, sociability, and well-being) and their eye movement behavior in an attempt to build a prediction model for visual design preferences. A total of 136 participants took part in this study. The feature selection and prediction of EI and eye movement data were performed using the genetic search method in conjunction with the bagging method. The results showed that participants high in self-control and emotionality exhibited different eye movement behaviors when performing five visual selection tasks. The prediction results (93.87% accuracy) revealed that specific eye parameters can predict the link between certain EI dimensions and preferences for visual design. This study adds new insights into human–computer interaction, EI, and rational choice theories. The findings also encourage researchers and designers to consider EI in the development of intelligent and adaptive systems.

Study on product form design via Kansei engineering and virtual reality

It is very important to predict the reaction of customers to future products. Sample pictures and line sketches are commonly used for discovering consumers’ demands. However, these two agents are difficult to express the real product form clearly and comprehensively, which may affect the accuracy of consumer affection prediction. In this paper, a method based on Kansei engineering via virtual reality (VR) has been proposed to construct a mapping relationship between form elements and consumer affection from four dimensions of the overall, unit, interrelation, and detail (OUID), so as to provide references for product form design. The correlation between product form elements and the perceptual image was studied with multiple linear regression analysis and partial correlation analysis. The different effects of VR, sketches, and pictures on user affection prediction were compared in this paper as well. A hairdryer has been employed as an example to illustrate the proposed method. The results show that compared with sketch and picture, VR based-prediction model is more accurate and reliable in predicting users’ emotional preferences. In addition to the unit form, the overall features, interrelation, and details are also the key factors affecting consumer preference. Highlight Based on Kansei Engineering, this paper investigated the correlation between the form elements of the product and the user's affection via VR. The proposed approach can help designers to quickly and accurately capture the user's perceptual image and transform it into design elements. The different effects of VR, sketches, and pictures on customer affection prediction were compared. A decomposition model is proposed to analyse the product form elements on four dimensions (overall features, unit form, interrelation, and details).

The influence of curvature and proportion on emotional preference for human-machine interface design

The influence of curvature and proportion on emotional preference for human-machine interface design

Effects of Low-Carbon Visualizations in Landscape Design Based on Virtual Eye-Movement Behavior Preference

Three-dimensional geovisualization in landscape design can be used to evaluate the efforts of mitigating CO2 emissions. This study evaluated subjects’ emotional preferences for 3D landscape design through an eye movement tracking experiment. In the case that the color of the building materials was positively correlated with low carbon emissions, green, blue, and gray were typical representatives of low carbon emissions. Through the eye movement tracking experiment, subjects’ emotional preferences for different building colors were obtained. The results show that the fixation trajectory is consistent with the preset green and energy saving parameters, and the design effect of the architectural landscape can be evaluated by detecting virtual eye movement tracking. There is a coupling relationship between virtual eye movement tracking, expert interviews, and evaluation results, so that it presents a logical relationship between virtual eye movement, the color of low-carbon materials, and carbon emissions. In addition, the affective preference analysis and entropy weight method confirmed their effectiveness in the evaluation of the 3D landscape design effect, which had a positive impact on the CO2 emission reduction of the construction industry. These results will contribute to the development of 3D landscape design in the architecture industry and provide new ideas and methods for the carbon peak project.

The interaction of emotions and cost-shifting rules in civil litigation

We model civil litigation as a simultaneous contest between a plaintiff and a defendant who have monetary and emotional preferences. The litigants’ emotional variables capture a non-monetary joy of winning and relational emotions toward each other. A contest success function (CSF) describes the litigants’ respective probabilities of success based on their endogenous litigation expenses and exogenous relative advantages. The model does not specify a functional form for the CSF. Instead, it accommodates any CSF that satisfies general and intuitive assumptions, which capture frequently-used functional forms. A cost-shifting rule allows the winner to recover an exogenous proportion of her litigation expenses from the loser. There exists a unique Nash equilibrium with positive expenses. In equilibrium, negative relational emotions (but not a positive joy of winning) amplify the effects of cost shifting, and vice versa. Thus negative relational emotions and positive cost shifting have a similar strategic role, and one can be a substitute for the other. If the litigants’ relative advantages are sufficiently balanced, then more cost shifting (or more negative relational emotions) increases total expenses in equilibrium.

The Influence of a School Social Network Intervention on Adolescent's Health Behaviors: A Gender-Specific Agent-Based Model.

IntroductionAdolescence is a crucial stage for health behavior development, which is associated with health in adulthood. School closures caused by the coronavirus disease 2019 (COVID-19) pandemic have exposed adolescents to an increased risk of obesity due to a lack of physical activity. Although social network interventions provide an effective approach for promoting health-related behavior, current practices neglect gender differences in adolescent behavioral patterns and emotional preferences. The aim of this study was to examine the effectiveness of centrality-based methods integrated with of gender contexts in a social network intervention to improve adolescent's health behavior.MethodsWe developed an agent-based model (ABM) that supports the small-world characteristics of adolescent social networks. Health-related data for junior middle school students (n = 234, 48% girls) were collected in November 2018, 2019 and 2020 in Tianjin, China. We simulated multiple network-based interventions with different criteria for influential agents (i.e., betweenness centrality, closeness centrality, eigenvector centrality, and PageRank) and a random condition. The rules for generating peer influence and accelerating behavioral changes were based on the diffusion of innovations theory, with gender specifications.ResultsAfter the school closures, there was a significant increase in the prevalence of overweight and obesity among adolescents, with a greater increase in girls than in boys (+8.85% vs. +1.65%, p < 0.001). Simulations showed that centrality-based network interventions were more effective than the random condition (average 6.17% per tick vs. 5.22% per tick, p < 0.05), with a higher efficiency in girls than boys (average 3.68% vs. 2.99% per tick, p < 0.05). PageRank outperformed other centrality conditions at the population level (6.37% per tick, p < 0.05). In girls, betweenness centrality was the best method (3.85% per tick, p < 0.05), while in boys, PageRank still had the greatest efficiency (3.21% per tick, p < 0.05).ConclusionsWe found evidence for gender differences in the negative impact of COVID-19-related school closures and the potential for centrality-based social network interventions to affect adolescent health behavior. Therefore, we emphasize the importance of gender-specific targeting strategies to further promote health-related school programs in the post-pandemic era.

A migratory behavior and emotional preference clustering algorithm based on learning vector quantization and gaussian mixture model

A migratory behavior and emotional preference clustering algorithm based on learning vector quantization and gaussian mixture model

Dispositional Mindfulness and Post-traumatic Stress Symptoms in Emergency Nurses: Multiple Mediating Roles of Coping Styles and Emotional Exhaustion.

ObjectiveTo explore the relationships between dispositional mindfulness (DM) and their post-traumatic stress symptoms (PTSS) of emergency nurses, and the mediating effects of coping styles and emotional exhaustion (EE).MethodsA cross-sectional survey study was conducted to collect data on DM, coping styles, EE, and PTSS among 571 emergency nurses from 20 hospitals in Chongqing, China. Correlation and structural equation models (SEMs) were used to evaluate the relationship among variables.ResultsEmergency nurses with lower dispositional mindfulness, higher emotional exhaustion and preference for negative coping (NC) revealed more PTSS. The effect of NC on PTSS was partially mediated by emotional exhaustion. Negative coping and emotional exhaustion played concurrent and sequential mediating roles between dispositional mindfulness and PTSS.ConclusionThis study has made a significant contribution to existing literature. It was suggested to develop interventions aimed at enhancing mindfulness, reducing negative coping strategies, and alleviating emotional exhaustion, which may be effective at reducing or alleviating post-traumatic stress symptoms of emergency nurses.

Music Emotion Research Based on Reinforcement Learning and Multimodal Information

Music is an important carrier of emotion and an indispensable factor in people’s daily life. With the rapid growth of digital music, people’s demand for music emotion analysis and retrieval is also increasing. With the rapid development of Internet technology, digital music has been derived continuously, and automatic recognition of music emotion has become the main research focus. For music, emotion is the most essential feature and the deepest inner feeling. Under the ubiquitous information environment, revealing the deep semantic information of multimodal information resources and providing users with integrated information services has important research and application value. In this paper, a multimodal fusion algorithm for music emotion analysis is proposed, and a dynamic model based on reinforcement learning is constructed to improve the analysis accuracy. The model dynamically adjusts the emotional analysis results by learning the user’s behavior, so as to realize the personalized customization of the user’s emotional preference.

A Novel Approach of Integrating Natural Language Processing Techniques with Fuzzy TOPSIS for Product Evaluation

Product designers need to fully understand consumers’ emotional preferences and responses for product forms to improve products. However, users and designers have different understandings and concepts in the product evaluation process, which will lead to cognitive asymmetry in the product design and evaluating process. This phenomenon prevents designers to grasp users’ needs, increasing the risk of product development failure. To this end, this paper proposes a product evaluation method that combines natural language processing techniques and fuzzy multi-criteria decision-making into a new integrated way to reduce the cognitive difference between users and designers, so as to solve the problem of cognitive asymmetry. This was done firstly by obtaining the review data of products from users on the Internet, based on a web crawler, and then constructing word vectors based on natural language processing techniques to realize the parametric expression of the Kansei image. Secondly, by using a statistical method to extract the product scheme that meets the preferences of users and designers, and then quantifying the relationship between the product form and Kansei image based on a grey relational analysis (GRA). Finally, by calculating the indicator weight based on the Entropy method and using the fuzzy TOPSIS method to explore the prioritization of the product design alternatives in view of the Kansei needs of users. Taking the smart capsule coffee machine as an example, the feasibility and effectiveness of this method are verified. In particular, the method proposed in this research can not only enable different cognitive subjects to achieve cognitive symmetry, but also filter out product forms that meet the cognitive needs of users. Moreover, this study provides a theoretical basis and practical significance for reducing the cognitive differences between cognitive subjects in the whole process of product design, and provides a systematic framework for the industry to effectively connect customer needs and product design decisions. At the same time, this study has introduced a new method for Kansei engineering.

Plant Colour Design and Healing Effect Based on Emotional Preference of Mental Sub-Health

Plant Colour Design and Healing Effect Based on Emotional Preference of Mental Sub-Health

Product recommendation using online reviews with emotional preferences

PurposeThe purpose of this paper is to develop a novel recommendation method using online reviews with emotional preferences for facilitating online purchase decisions. This leads to better use of information-rich online reviews for providing users with personalized recommendations.Design/methodology/approachA novel method is developed for producing personalized recommendations in online purchase decision-making. Such a method fuses the belief structure and the Shapley function together to effectively deal with the emotional preferences in online reviews and adequately tackle the interaction existent between product criteria with the use of a modified combination rule for making better online recommendations for making online purchase decisions.FindingsAn example is presented for demonstrating the applicability of the method for facilitating online purchase. The results show that the recommendation using the proposed method can effectively improve customer satisfaction with better purchase decisions.Research limitations/implicationsThe proposed method can better utilize online reviews for satisfying personalized needs of consumers. The use of such a method can optimize interface design, refine customer needs, reduce recommendation errors and provide personalized recommendations.Originality/valueThe proposed method adequately considers the characteristics of online reviews and the personalized needs of customers for providing customers with appropriate recommendations. It can help businesses better manage online reviews for improving customer satisfaction and create greater value for both businesses and customers.

Research on the spatial characteristics of sky gardens based on networked pictures: a case study of Singapore

ABSTRACT As alternative public spaces in vertical public realms, sky gardens have become an increasingly important spatial element and part of the urban vocabulary in high-density environments worldwide. However, the public's spatial experience, social behavior and aesthetic needs in sky gardens have not been thoroughly explained. This paper takes Singapore, which has a rich social public space in the air, as an example where studies estimating spatial perception have used networked images instead of user preference survey results. Manual image identification and image recognition were performed with a computer vision application programming interface (API) to recognize networked images. Then, we extracted the sky gardens’ main elements in Singapore’s urban environment using clustering analysis, principal component analysis and factor analysis with SPSS. Finally, we discuss the spatial distribution, role and composition of sky gardens in high-density cities and people’s emotional preferences. The study shows that sky gardens are effective alternative public spaces in Singapore's vertical city, and their physical elements occupy a dominant position in the public’s spatial perception; there is a strong tendency for different buildings’ sky gardens to have spatial demand characteristics, while public facilities and cultural activities are key factors that affect sky gardens’ quality.

Effect of Horticultural Activities on Emotional Intelligence and Plant Preference in Children

Effect of Horticultural Activities on Emotional Intelligence and Plant Preference in Children

Misattribution of duties as free choices: The role of emotional awareness in self-infiltration

Individuals sometimes mistake others' expectations or imposed duties for self-chosen goals, even though they are not congruent with their emotional preferences or integrated values—a phenomenon coined as self-infiltration. Previous studies demonstrated that self-infiltration is more likely to occur in individuals with reduced self-regulation abilities. Here, we investigated in a sample of 250 students whether this association may be mediated by trait emotional awareness, the ability to recognize and understand one's emotions. This mediation hypothesis could be confirmed. We discuss our findings with respect to their potential relevance for research on motivated goal pursuit and health and practical applications.

Emotion Analysis of Personalized Color of Beauty Package Based on NCD Image Positioning.

Purpose: Based on the Nippon Color & Design (NCD) system, this study aims to accurately discover the color preferences and image positioning of different female groups in China and, thus, to establish a color reference system, which is suitable for the packaging of beauty products.Methods: We first selected middle-aged women in the rural area of northern China as the studied group. Then, we conducted an extensive questionnaire survey on their color preferences focusing on their psychological characteristics and perception rules of emotional needs for colors. After that, we extracted colors from samples and classified them using the NCD system research method. Finally, we conducted a systematic analysis and verification to determine the color emotional preference of this group.Conclusion: We investigate the color preference of targeted customers to establish the image space of beauty product packaging. By applying SPSS for the factor analysis, we study the rural women in northern China, who are less concerned about fashion. We focus on the accurate positioning between the interaction of color, women, and environment throughout the color design process. We have conducted a series of comparative analyses of popular beauty products among the rural women. The results can accurately reflect the brand definition and positioning of color semantics and, thus, provide invaluable information for future beauty packaging designs and marketing promotion strategy.