Emotional Preferences Research Articles

Towards Emotionally Intelligent Virtual Environments: Classifying Emotions through a Biosignal-Based Approach

This paper introduces a novel method for emotion classification within virtual reality (VR) environments, which integrates biosignal processing with advanced machine learning techniques. It focuses on the processing and analysis of electrocardiography (ECG) and galvanic skin response (GSR) signals, which are established indicators of emotional states. To develop a predictive model for emotion classification, we extracted key features, i.e., heart rate variability (HRV), morphological characteristics, and Hjorth parameters. We refined the dataset using a feature selection process based on statistical techniques to optimize it for machine learning applications. The model achieved an accuracy of 97.78% in classifying emotional states, demonstrating that by accurately identifying and responding to user emotions in real time, VR systems can become more immersive, personalized, and emotionally resonant. Ultimately, the potential applications of this method are extensive, spanning various fields. Emotion recognition in education would allow further implementation of adapted learning environments through responding to the current emotional states of students, thereby fostering improved engagement and learning outcomes. The capability for emotion recognition could be used by virtual systems in psychotherapy to provide more personalized and effective therapy through dynamic adjustments of the therapeutic content. Similarly, in the entertainment domain, this approach could be extended to provide the user with a choice regarding emotional preferences for experiences. These applications highlight the revolutionary potential of emotion recognition technology in improving the human-centric nature of digital experiences.

Beyond Happiness: Toward a Resource-Based Understanding of Emotional Preferences

Beyond Happiness: Toward a Resource-Based Understanding of Emotional Preferences

Negative images, regardless of task relevance, distract younger more than older adults.

Older adults, compared to younger adults, tend to prioritize positive information more and negative information less. We recently observed this "positivity effect" pattern in an emotion-induced blindness task, which measures attention allocated to task-irrelevant emotional stimuli in the way participants are distracted by them. Older adults were less distracted by negative images compared to younger adults. This could represent an age-related priority shift away from negative emotions. However, it could also be that older adults simply do not see negative images presented at a fast rate. A similar possibility is that older adults to fail to engage with negative stimuli because of their complex nature, rather than due to age-related changes in emotional preference per se. In the present study, we tested this possibility by manipulating the required degree of engagement with emotional distractors. Participants completed a modified emotion-induced blindness task, with emotional distractors that were either task irrelevant (younger: n = 48; older: n = 46) or task relevant (younger: n = 48; older: n = 45). The task relevance of distractors did not affect performance. Even though older adults could quickly perceive the negative images, they were less distracted by them compared to younger adults. Current theories of the positivity effect fail to fully account for these positivity effect patterns in attention, especially those that propose mechanisms requiring a substantial time to enact. The current results may require rethinking previous accounts of the positivity effect and highlight the benefits of probing the positivity effect in early cognitive processing stages. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Social Media Users’ Visual and Emotional Preferences of Internet-Famous Sites in Urban Riverfront Public Spaces: A Case Study in Changsha, China

With the increasing online exposure of urban public spaces, the new concept of “internet-famous sites” has emerged in China. Social media users are the main contributors to this new phenomenon. To fully understand social media users’ preferences in such kinds of public spaces, this article took 27 typical riverfront internet-famous sites (RIFSs) in Changsha City (China) as an example. Through social media platform selection, keyword research, text and image data extraction, visual and emotional symbol coding, and manual calculations of coding frequency, this study investigated social media users’ perception of RIFSs, especially on visual and emotional preferences. The online images and review comments were extracted from the popular Chinese social media platform “Xiaohongshu”. We found that (1) the popularity of each RIFS had a significant head effect and there were far more positive emotions than neutral and negative emotions in review comments. (2) RIFSs in Changsha were divided into five categories: commercial RIFSs, art exhibition RIFSs, historical and cultural RIFSs, ecological recreational RIFSs, and uncultivated RIFSs. Social media users had different visual focuses on each kind of RIFS. (3) Social media users provided specific reasons for their emotional preferences towards different types of RIFSs. This study can provide a new perspective on improving waterfront vitality and offer a targeted and attractive method for waterfront regeneration that is different from traditional methods.

The semantic role of traditional music culture in the nomadic mentality of the Kazakhs

Relevance. Value orientations formed by centuries of historical and cultural experience characterise the deep level of collective and individual consciousness, mentally they are people's life and practical attitudes, emotional preferences, and stable images of the world, peculiar to a given community and its cultural tradition. Mentality also plays a decisive role in developing and forming ethno-cultural identity. Purpose. The article aims to consider some peculiarities of the nomadic mentality of the Kazakhs, manifested in the content of music and traditional art of the Kazakhs, as well as in the world of feelings, emotions and beliefs, bonded by the idea of unity of nature and man. Methodology. The study analyses the content of music and traditional art of the Kazakhs. Results. The nomadic mentality of Kazakhs is deeply embedded in their musical culture, influencing its genesis and continuing to shape its expression today. Besides, nowadays, in the century of global transformations and integrations, the understanding of the nature of a traditional nomadic mentality can become one of the ways to a meaningful movement towards modernization and a dialogue of the world cultures, based on the respect of the national cultural values. Conclusions. Thus, the article highlights the importance of making musical cultural traditions a powerful tool for self-development and preservation of ethnic and cultural identity. The necessity of this tool has become even more comprehensible in the 21st century, the age of unification of cultures. Keywords: nomadic mentality; traditional Kazakh culture; language and mentality; value orientations; art; being; transformation; post-civilisation.

The world from the perspective of digital nomads: exploring sentiments in destination reviews

PurposeThis study aims to explore the emotional landscapes and spatial preferences of digital nomads, focusing on how sentiments expressed in destination reviews influence their mobility and destination choices.Design/methodology/approachEmploying a lexicon-based sentiment analysis of social media comments and reviews, alongside advanced geographical information systems (GIS) mapping techniques, the study analyzes the emotional tones that digital nomads associate with various destinations worldwide.FindingsThe analysis reveals significant patterns of emotional sentiments, with trust and joy being predominant in preferred destinations. Spatial patterns identified through GIS mapping highlight the global distribution of these sentiments, underscoring the importance of emotional well-being in destination choice.Practical implicationsInsights from this study offer valuable guidance for Destination Management Organizations (DMOs) in strategic planning, enhancing destination appeal through targeted marketing strategies that resonate with the emotional preferences of digital nomads.Originality/valueThis research introduces a novel approach by integrating sentiment analysis with GIS to map the emotional and spatial dynamics of digital nomadism, contributing a new perspective to the literature on tourism and mobility.

Constructing a MOEA approach for product form Kansei design based on text mining and BPNN

Kansei Engineering (KE) is a product design method that aims to develop products to meet users’ emotional preferences. However, traditional KE faces the problem that the acquisition of Kansei factors does not represent the real consumers demands based on manual and reports, and using traditional methods to calculate relationship between Kansei factors and specific design elements, which can lead to the omission of key information. To address these problems, this study adopts text mining and backward propagation neural networks (BPNN) to propose a product form design method from a multi-objective optimization perspective. Firstly, Term Frequency-Inverse Document Frequency (TF-IDF) and WordNet are used to extract key user Kansei requirements from online review texts to obtain more accurate Kansei knowledge. Secondly, the BPNN is used to establish the non-linear relationship between product Kansei factors and specific design elements, and a preference mapping prediction model is constructed. Finally, BPNN is transformed into an iterative prediction value of non-dominated sorting genetic algorithm-II (NSGA-II), and the model is solved through multi-objective evolutionary algorithm (MOEA) to obtain the Pareto optimal solution set that satisfies the user’s multiple emotional needs, and the fuzzy Delphi method is used to obtain the best product form design scheme that meets the user’s multiple emotional images. Using the example of electric bicycle form design could show that this proposed method can effectively complete multi-objective product solutions innovation design.

Intrinsic beauty and emotional experiences: How beach appeal shapes tourists’ revisit intentions in emerging coastal destinations in Ghana

The study aims to explore the tourists’ emotional response factors associated with the intrinsic beauty and values of beaches at emerging coastal destinations. The study also examines the influence of tourists’ emotional response factors on revisit intentions. Data collected from 602 tourists at Ghanaian beaches were analyzed using Factor Analysis and the Binary Probit Model in STATA. The research identifies seven emotional experience factors: joy, serenity, awe, longing, love, sadness, and regret, which are associated with the intrinsic beauty and value of the beach. The findings also reveal that the emotional experiences of joy, serenity, longing, and sadness significantly influence beach tourists’ intentions to revisit emerging beach destinations. Beach destination management should, therefore, adopt sustainable practices that align with tourists’ emotional preferences and leverage nostalgia-inducing elements of beach destination attributes.

Differences in Emotional Preferences toward Urban Green Spaces among Various Cultural Groups in Macau and Their Influencing Factors

This study explores the diversity in emotional tendencies and needs toward urban green spaces (UGSs) among people from different cultural backgrounds in the wave of cultural integration. We utilized social media data as research tools, gathering a wide range of perspectives and voices. Utilizing geolocation data from 176 UGSs in Macau, we collected 139,162 social media comments to analyze the emotional perceptions of different cultural groups. Furthermore, we conducted regression analysis on the number of posts and emotional intensity values from four linguistic groups—Chinese, English, Southeast Asian languages, and Portuguese—in UGSs, correlating them with ten locally relevant landscape features. Our findings reveal diverse attitudes, emotional inclinations, and functional and design needs of different linguistic groups toward UGSs, as follows: (1) there were significant differences in emotional intensity and tweet counts across 176 UGSs; (2) Chinese and Portuguese speakers showed a more positive attitude toward plazas and natural ecological areas, whereas English- and Southeast-Asian-language speakers tended to favor recreational areas and suburban parks; (3) Chinese speakers exhibited a more positive emotional intensity toward sports facilities, while English speakers placed more emphasis on green space areas, architecture, sports infrastructure, and plant landscapes; (4) there was no specific landscape feature preference for Portuguese- and Southeast-Asian-language speakers. This research not only deepens our understanding of the emotional perceptions and preferences of UGSs among different cultural groups but also explores the association between these groups and various urban landscape features. This provides important theoretical and practical insights for future UGS planning, construction, and promoting multicultural coexistence for sustainable urban development.

Identifying positive and negative comments underneath technology videos based on Bert's model

With the gradual popularization of the Internet and the increasing richness of content, more and more popular science videos appear in peoples vision. However, people have different attitudes towards them and cannot make explicit judgments. This paper used comments from some popular science videos on Bilibili as a dataset, trained the Bert model using parallel training methods such as (Distributed Data parallel) DDP, and selected different proportions of datasets (20%, 30%, and 40%) for training and testing data to objectively determine the positive and negative attitudes of people in comments. Research has found that different scale datasets have similar performance, with an 86% -87% accuracy rate. Besides, multi-card parallel processing can bring higher returns. The results help people comprehensively understand audience feedback and emotional preferences towards technical content. At the same time, it reveals the complex relationship between the emotions reflected in comments and various factors such as audience engagement, content strategies, and demographics.

Machine Learning-Based Classification of Turkish Music for Mood-Driven Selection

Music holds a significant role in our daily lives, and its impact on emotions has been a focal point of research across various disciplines, including psychology, sociology, and statistics. Ongoing studies continue to explore this intriguing relationship. With advancing technology, the ability to choose from a diverse range of music has expanded. Recent trends highlight a growing preference for searching for music based on emotional attributes rather than individual preferences or genres. The act of selecting music based on emotional states is important on both a universal and cultural level. This study seeks to employ machine learning-based methods to classify four different music genres using a minimal set of features. The objective is to facilitate the process of choosing Turkish music according to one’s mood. The classification methods employed include Decision Tree, Random Forest (RF), Support Vector Machines (SVM), and k-Nearest Neighbor, coupled with the Mutual Information (MI) feature selection algorithm. Experimental results reveal that, with all features considered in the dataset, RF achieved the highest accuracy at 0.8098. However, when the MI algorithm was applied, SVM exhibited the best accuracy at 0.8068. Considering both memory consumption and accuracy, the RF method emerges as a favorable choice for selecting Turkish music based on emotional states. This research not only advances our understanding of the interaction between music and emotions but also provides practical insights for individuals who want to shape their music according to their emotional preferences.

Effect of material properties on emotion: a virtual reality study.

Designers know that part of the appreciation of a product comes from the properties of its materials. These materials define the object's appearance and produce emotional reactions that can influence the act of purchase. Although known and observed as important, the affective level of a material remains difficult to assess. While many studies have been conducted regarding material colors, here we focus on two material properties that drive how light is reflected by the object: its metalness and smoothness. In this context, this work aims to study the influence of these properties on the induced emotional response. We conducted a perceptual user study in virtual reality, allowing participants to visualize and manipulate a neutral object - a mug. We generated 16 material effects by varying it metalness and smoothness characteristics. The emotional reactions produced by the 16 mugs were evaluated on a panel of 29 people using James Russel's circumplex model, for an emotional measurement through two dimensions: arousal (from low to high) and valence (from negative to positive). This scale, used here through VR users' declarative statements allowed us to order their emotional preferences between all the virtual mugs. Statistical results show significant positive effects of both metalness and smoothness on arousal and valence. Using image processing features, we show that this positive effect is linked to the increasing strength (i.e., sharpness and contrast) of the specular reflections induced by these material properties. The present work is the first to establish this strong relationship between specular reflections induced by material properties and aroused emotions.

Multidimensional Scale Analysis and Modeling of Emotional Space in Yao Music

Abstract The research content of this paper gives a detailed analysis of the system structure of the music emotion recognition system. In the process of music feature extraction and recognition, the system first reads the note queue and tempo information queue of the format music and then analyzes and calculates the basic features of the music, tonal and melodic features, etc., respectively. The content of the text set is projected into a three-dimensional visual space using the multidimensional scale analysis method, and then the emotional theme is obtained by dividing the class groups. The samples from the Yao music database are selected as the data source for music emotion research, and performance analysis is performed. The results prove that the method of this paper can effectively perform feature extraction on Yao music files, with an average misdetection rate of only 0.09% and a recognition rate of more than 83% in all cases. The musical structure of Yao Village Impression can be broken down into five parts. The musical melodies mostly consist of major second and minor third intervals. The emotional labeling of structures 1 and 4 in the cluster analysis is distributed in four quadrants, with a preference for pleasurable emotions. Structure 2 was more concentrated in quadrants 1, 4. These emotion distribution results are consistent with the music depicting the beauty of Yao village and the emotional life of Yao people.

초등학교 1학년 한글해득부진 아동과 일반 아동의 영역별 발달과 유아기 가정 문해환경 비교

The current study compares the developmental levels in different facets under Hangeul acquisition and home literacy environment (HLE) during the preschool period of children in their first grade who had Hangeul acquisition difficulties and those who did not. Study participants included 99 pairs of first graders with Hangeul acquisition difficulties and their mothers, 140 pairs of first graders without such difficulties and their mothers, and 70 teachers. Analysis of covariance and dependent samples t-test showed develop-ment levels in language, literacy, preference for conventional literacy activities, cognition, sociality, and/or emotion were statistically lower in children with Hangeul acquisition difficulties. Additionally, the same children experienced poorer quality HLEs during their preschool period compared to their counterparts, indicating lower levels of emergent liter-acy guidance. However, preference for emergent literacy activities and certain HLEs dur-ing preschool period (literacy interaction, picture book reading interaction, conventional literacy guidance) did not show significant gaps between the two groups. The findings of this study suggest the need for support for families with poorer HLEs before entering school age, and a comprehensive plan to help the holistic development of children who show difficulties in Hangeul acquisition.

방치된 주유소의 적응적 재사용을 위한 생활플랫폼 사례연구

Gas stations, which are essential urban infrastructure, are under pressure to spread new transportation methods and quickly replace infrastructure due to recent research and technological advancements in alternative energy such as hydrogen and electricity. This economic burden is rapidly increasing the closure and neglect of gas station spaces. Because abandoned gas stations cause environmental harm from pollution, social risk from crime, and deterioration of the city's image, the public sector must view this as an urban problem and respond actively and quickly to resolve it. Adaptive reuse is a tool to revitalize a city in stagnation by eliminating psychological instability found in local idle space and improving physical inconveniences, providing a space with new functions tailored to the needs of local residents. Accordingly, this study studied the case of a lifestyle platform that is rapidly expanding into people's daily lives as we enter the leisure culture era. The purpose of this study was to consider the possibility of utilizing neglected gas station space from the perspective of conversion into a lifestyle platform appropriate for the times, and to present the basic direction of an adaptive reuse plan that reflects this result. In conclusion, abandoned gas stations are sufficiently adaptive and reusable spaces by taking steps to explore influencing factors, establish design standards, and prepare operating standards, but they must be improved by utilizing the characteristics of the physical space but reflecting emotional preference factors. The gas station space transformed into a lifestyle platform can become a place of daily life by providing local residents with environmental comfort, stability of access, and diversity of experiences that were not possible when it was an abandoned gas station.

Applying a Kansei engineering-based relationship model design approach to developing consumers' sustainability reliance on apparel

PurposeBased on Kansei Engineering, this study obtained consumers' emotional preferences aiming to enhance the emotional connection between consumers and clothing to extend the service life of clothing and realize sustainable clothing design.Design/methodology/approachSix Kansei word pairs that are the most important to consumers were identified through literature reviews, magazines, websites, card sorting of consumers and cluster analysis. Finally, the consumers scored the 32 product specimens through a 5-level rating semantic differential scale questionnaire of six Kansei word pairs. The researchers verified the consumers' emotional preferences through principal component analysis and established the relationship between Kansei words and design elements of color through partial least squares.FindingsThe study found consumers' emotional preferences: elegant, minimalist, formal, casual, mature, practical and distinctive style. Besides white, black, gray, blue, consumers will also like red and yellow-red in the future. The crucial findings of this study are to get recommended guidelines that consumers' emotional preferences match the corresponding design elements.Originality/valueThe study's findings can be used to style the design of men's plain-color shirts and guide online marketers and designers to design apparel that meets consumers' emotional needs to develop consumers' sustainability reliance on clothing. This study also explains the overall process and methodology for integrating consumer preferences and product design elements.

EMOTIONAL COMPONENT OF FUTURE CHOREOGRAPHERS’ AESTHETIC CULTURE: ESSENCE, INDICATORS OF FORMATION, RESULTS OF THE DIAGNOSTIC EXPERIMENT

The experimental article highlights the essence of the emotional culture of students of higher education in the specialty 024 Choreography, indicators of the formation of its emotional component (emotional-aesthetic sensitivity, ability to aesthetic pleasure, the aesthetic emotional orientation of the personality), diagnostic methods (test questionnaire B. Dodonov “Emotional Orientation,” questionnaire by B. Bass, questionnaire by M. Rokych, included observation, mini-work “My impressions”) and its results. The levels of formation of the emotional component of the aesthetic culture of future choreographers in the experimental (EG) and control groups (CG) have been determined: a high level was demonstrated by 11.43% of the EG students and 14.71% of the CG; average – 22.86% and 23.53%, respectively; low – 65.71% and 61.76%). The rating of the emotional orientation of the personality in future choreographers is presented, such as praxic, gloristic, hedonistic, communicative, pugnacious, aesthetic, romantic, altruistic, acquisitive, and gnostic. The spaces of emotional preferences of students have been analyzed. It has made it possible to draw up a strategy for the formation of future choreographers’ aesthetic culture in a higher education institution: 1) students of higher education have a rich emotional sphere as a basis for the formation of the studied professional and personal quality in them; 2) aesthetic emotions have an intermediate character in the hierarchy of students’ emotional values, therefore, under favorable conditions of their aesthetic development, they can acquire a higher status, which corresponds to representatives of artistic professions; 3) the dominance in the sample of the practical and gloristic orientation of the personality aims at the application of active methods and techniques, pedagogical support technology based on the student-centered approach in experimental work.

Personalized Art Work Recommendation System and Methods Based on User Interest Characteristics and Emotional Preferences

To familiarize users with their interests and hobbies through online data collection, and improve their experience when browsing art works, research based on K-means algorithm has received widespread attention. However, with the explosive growth of various types of art works, it is difficult to estimate the K value of the K-means algorithm when processing these data. To solve this problem, this research predicts the user behavior of Wink dataset based on K-means algorithm, introduces regularization specified process and emotional precision, and generates fusion algorithm. The study first proposes the concept of similar users and calculates the Pearson correlation coefficient between them to determine their similarity; Then several regularization terms are added to the user group, and the prediction results are obtained by changing the parameters; Further screening of art works clustering categories is to address the issue of slow user startup. Finally, the algorithm studied will be applied to the Wink dataset and the prediction accuracy of the particle swarm optimization algorithm will be tested and compared with the fusion algorithm. A total of 400 experiments are conducted, and the fusion algorithm achieve a prediction accuracy of 392 times, with an accuracy rate of 98.0%; The accuracy of particle swarm optimization algorithm is close to that of fusion algorithm, at 88.2%. The experimental results show that the algorithm model proposed in the study can effectively map the relationship between user interest features, emotional factors, and personalized art recommendation, thereby providing users with a good viewing experience.

NLP-based approach for automated safety requirements information retrieval from project documents

Numerous project documents generated during the construction phase pertain to the actual safety requirements (SRs) specified by project managers (PMs), and these concealed requirements can aid in making safety decisions if accurately identified and utilized. However, PMs’ requirements are frequently recorded informally in project documents, necessitating extensive manual analysis to guide safety management practices. To address this limitation, this study developed a natural language processing (NLP)-based framework of requirement retrieval and document association (RRDA) to mine requirements and retrieve requirement-related documents. In particular, requirement-document (RD) association rules are designed to retrieve the requirement-related documents. The results demonstrate that our framework can retrieve the PMs’ requirements with a maximum ontology relevance of 91.37% and emotional preference of requirement with a maximum semantic tendency intensity of 0.91. The presented algorithm shows satisfactory performance in the number of iterations and threshold, and there are outstanding advantages in model training comparison. Additionally, there is a significant degree of matching between the retrieved documents and the requirements, which has significant managerial implications for requirement-oriented construction safety management.

The Influence of Status Quo Bias in Marketing and Reasons Leading to this Tendency

Status quo bias refers to the emotional preference to the present situation. It could also be defined as the tendency to resist changes, even there are better alternatives being provided. Status quo bias significantly influences individuals behavior in variously fields. This essay mainly investigated the extent of status quo bias, affecting consumers purchasing preferences in marketing, as well as the reasons behind. Through the study on historic concepts, analysis on typical cases and 2 specially designed experiments, the conclusion reached is that status quo bias is consistently influential in marketing, and reasons include preference to familiar subjects and aversion of lost. Based on the previous theories and studies, typical case (Coca-Cola, 1985) is analyzed and online experiments are designed to illustrate the reasons people choose status quo when facing consumption choices. Results show that status quo bias is consistently influential in marketing, due to loss aversion, cognitive tendency and the rejection of risk and uncertainty. Enterprises therefore could use status quo bias as an effective selling strategy, in order to increase sales and profits.