User Emotions Research Articles

A Case Study in Natural Fibre Material (Luffa Sponge) Development Using E2-Material-Driven Design

To unleash the emotional potential of natural fibre materials in sustainable development and utilisation, this paper presents a material-driven design method with emotional and ecological indicators (E2-MDD). The method offers product-level solutions for the sustainable development of natural materials. The method involves several steps, such as screening the main material quality, capturing the user emotion vision, deconstructing the E2 vision pattern, and deducting the product design concept. The method was tested on luffa sponge samples, seen as one kind of traditional fibre resource, which resulted in four differentiated schemes, which were evaluated using the E2-MDD ring radar column score chart. The study identified three key emotional qualities for natural fibre materials: associativity, uniqueness, and biophilicity. The results show that product concepts closer to the natural material’s original form scored higher, while the inclusion of non-natural materials had a negative impact on the evaluations. This study also found that E2-MDD could strengthen the emotional and ecological connection between people and products, further indicating that material and design can establish a link between environmental friendliness and emotional experience. Lastly, the paper suggests future development areas for the E2-MDD method, including focusing on users, ecology, and business.

Research on emotion modeling of intelligent agents in earthquake evacuation simulation

In recent years, virtual reality (VR) has been widely used in emergency drills, skills training and other fields of science education. However, existing VR emergency training platforms lack intelligent agents endowed with emotional and cognitive abilities, making them challenging to evoke user emotions and achieve immersion. Moreover, existing emotion contagion methods of virtual agents lack analysis on whether the emotions of virtual agents can infect users in the real world. Therefore, we proposed an emotional cognitive model (ECM) that simulates the emotional contagion of intelligent agents in a VR earthquake emergency training platform. To evaluate the proposed model, we conducted a user study requiring the user to control an avatar for evacuation training during a simulated earthquake. The user’s brain signals are measured using EEG, fNIRS, and eye-tracking devices to analyze whether the user was affected by the emotions of other intelligent agents. The results show that intelligent agents with emotional cognition can evoke user’s emotions in earthquake emergency training.

A model for early rumor detection base on topic-derived domain compensation and multi-user association

In the era of rapid Internet development, social networking sites have become breeding grounds for rumors. Detecting and addressing these rumors early is crucial to mitigate the potentially devastating consequences they may bring. This paper presents an innovative model for early rumor detection to tackle the challenge posed by sparse data in the early stages of rumor outbreaks. Firstly, a content-based method for data compensation is proposed, considering the feature correlation between the original and derived topics. The method effectively matches derived topics based on the content features of the topics, thereby enriching the original domain and solving the challenge of data sparsity. Secondly, a method for constructing the network structure is proposed to tackle the issue of user association within the early topic domain. This method introduces a quantification approach to evaluate the association relationship among multiple users. By incorporating game theory to quantify user emotion, the method effectively transforms the topic domain into a multi-user relationship network with a non-Euclidean structure. Finally, leveraging the capabilities of Graph Convolutional Networks (GCN) to process non-euclidean data, a novel early rumor detection model, namely DDCA-GCN, is proposed. It combines the strategies of topic-derived domain compensation and the principle of multi-user correlation. It can effectively identify early rumors and simultaneously comprehensively analyze users’ responses. The experimental results successfully demonstrate the feasibility of incorporating derived topic elements for early rumor detection. This validation underscores the effectiveness of leveraging derived topic domains to bolster the accuracy and timeliness of rumor detection.

Effects of product personalisation degree on user perception in car front design

The front facia gives the car vivid features; accordingly, and an appropriate product personalisation degree (PD) can improve product branding, related to the appearance design, while avoiding excessive design features. This study investigates the effects of the car front facia PD on user perceptions and proposes design guidelines for vehicle designers and manufacturers. An open-ended experiment was conducted with 30 participants using 60 car fronts to study user emotions and preferences related to product personality based on questionnaire and physiological electrical signal evaluation results. The features were extracted using the chaos theory and cvxEDA algorithm. The obtained results indicate that the PD was consistent with user emotions. Furthermore, when the consistency between PD and user emotions is high, a significant variation in user preferences can be observed. Therefore, when designing high-PD products, the sub-item product personalisation degree (sub-item PD) should be carefully managed, considering the overall logic and coherence. Highlights Product personalisation degree is positively correlated with the subjective and objective emotions of users. The impact of product personalisation degree on user preferences and subjective emotions is not always the same, particularly pleasure and arousal. When product personalisation degree is highly correlated with the subjective and objective emotions of users, the user preferences are highly differentiated.

Elevating metaverse virtual reality experiences through network‐integrated neuro‐fuzzy emotion recognition and adaptive content generation algorithms

AbstractInteractions between individuals and digital material have completely changed with the advent of the Metaverse. Due to this, there is an immediate need to construct cutting‐edge technology that can recognize the emotions of users and continuously provide material that is relevant to their psychological states, improving their overall experience. An inventive method that combines natural language processing adaptive content generation algorithms and neuro‐fuzzy‐based support vector machines natural language processing (SVM‐NLP) is proposed by researchers to meet this demand. With this merging, the Metaverse will be able to offer highly tailored and engaging experiences. Initially, a neuro‐fuzzy algorithm was developed to identify people's emotional moods from their physiological reactions and other biometric information. Fuzzy Logic and Support Vector Machine work together to manage the inherent ambiguity and unpredictability, which results in a more exact and accurate categorization of emotions. A key component of the ACGA is NLP technology, which uses real‐time emotional data to dynamically modify and personalize characters, stories, and interactive features in the Metaverse. The novelty of the proposed approach lies in the innovative integration of neuro‐fuzzy‐based SVM‐NLP algorithms to accurately recognize and adapt to users' emotional states, enhancing the Metaverse experience across various applications. The proposed method is implemented using Python software. This adaptive approach significantly enhances users' immersion, emotional involvement, and overall satisfaction within the augmented reality environment by tailoring information to their responses. The findings show that the SVM‐NLP emotion identification algorithm based on neuro‐fuzzy, has a high degree of accuracy in recognizing emotional states, which holds promise for creating a Metaverse that is more emotionally compelling and immersive. Stronger human–computer interactions and a wider range of applications, including virtual therapy, educational resources, entertainment, and social media networking, might be made possible by integrating SVM‐NLP. These sophisticated systems are around 92% accurate in interpreting the emotions.

The Determinant Factors of Shopping Cart Abandonment Among E-commerce Customers in Indonesia

Predicting the non-purchase behavior of potential customers, such as the abandonment of online shopping carts, is a pivotal factor in determining the success of companies. Despite several conducted studies, further investigation is still required to gain a profound understanding of the underlying causes of these phenomena. The research aims to analyze the motivating factors behind shopping cart abandonment among ecommerce customers in Indonesia using a quantitative method. Furthermore, the population size is undefined, and the sample consists of 200 respondents selected through purposive sampling. The sample size is determined by five times the indicator number. The data analysis is conducted using Structural Equation Modeling (SEM) through SmartPLS 4.0.8.5, and the Coefficient of determination (R2) value for shopping cart abandonment is found to be 37.5%. The results show that complicated checkout, information overload, complicated policies, and limited shipping options positively impact shopping cart abandonment. Complicated checkout emerges as the most significant variable. Meanwhile, perceived cost and emotional ambivalence have no impact. The research also provides theoretical contributions and suggests future research for e-commerce companies and merchants. The theoretical contribution is how user emotions, user experience, merchant policies, and e-commerce regulation affect shopping cart abandonment. From the practical implications, e-commerce companies should focus on the user experience during checkout to reduce shopping cart abandonment.

Impact of mobile application loading icon type and animation frequency on user time perception and emotion

As the status indicator of system programs, loading icons have a significant role in human–computer interaction. This study explored the effect of the visual presentation of mobile application loading icons on users' time perception and emotion. The two variables adopted in this experiment were the type of loading icons and the animation frequencies. Three types of loading icons were used: circle type, aligned dots type, and logo type. Four frequencies were chosen: 3 Hz, 2 Hz, 1.5 Hz, and 1 Hz (changing every 333 ms, 500 ms, 666 ms, and 1000 ms). Theories related to subjective temporal experience and the three-dimensional emotion model of pleasure-arousal-dominance were utilized in this experiment to measure the user's time perception and emotion comprehensively. The experiment in this study was a 3x4 within-subject design. A total of 67 university students aged 18–26 participated in this experiment. The results showed that users' time perception and emotions were influenced by icon types and animation frequencies. Users who experience logo type icons were more inclined to generate positive evaluations. Loading icons with higher animation frequency had more positive user perception evaluation, but for more complex icons, excessively high animation frequency probably led to a negative visual experience. These findings might help improve the waiting experience of users when using the applications.

The Impact of AI on Human Roles in the User Interface & User Experience Design Industry

The ever-evolving field of User Interface & User Experience UI/UX design prioritizes creating user-friendly interfaces. Traditionally, this has been a human-centred process. However, Artificial Intelligence AI offers new possibilities for automating design tasks and leveraging data for user insights. This research paper delves into the potential impact of AI on UI/UX design. The core question is whether AI tools can effectively replace human designers in crafting user experiences. Alternatively, can AI work alongside designers to enhance their capabilities? This paper explores these questions through a review of existing research and proposes a research methodology to further investigate the topic. The literature review analyses how AI can be used for tasks like user behaviour analysis, A/B testing, and prototype generation. However, it also acknowledges AI's limitations in understanding user emotions, implementing creative solutions, and adapting to unforeseen user needs. The suggested research methodology will give a combined approach, making a review of existing literature with interviews from UI/UX professionals and a case study analyzing a design project utilising AI tools. By investigating the strengths and limitations of AI in design tasks, how AI can be integrated into the workflow, and the ethical considerations surrounding AI-driven design decisions, this research helps to provide a better understanding of the relationship between AI and human designers in the UI/UX field. The findings can inform design education, industry practices, and the development of future AI tools specifically tailored for UI/UX design applications. Keywords: UI/UX Design, Artificial Intelligence, Human-Computer Interaction, User Experience, User Interface, Design Automation

Research on Barrage Text Mining and Emotional Orientation in Online Interactive Learning Videos: Based on the Case Study of "Luo Xiang's Criminal Law"

This study uses text mining and sentiment analysis methods to analyze the barrage text information of "Luo Xiang's Criminal Law" online teaching videos and sort out the main emotional tendencies of users. The research found that user emotions change with the dispersion of hot topics, showing a decentralized characteristic, and at the same time, users still have a certain lack of capture for the content of online teaching videos in the interactive learning process. It is urgent to clarify the specific impact of technology on users. This study is helpful for deepening research on online interactive learning, clarifying user emotional tendencies, and providing a decision-making basis for accurately improving interactive learning effects.

Ukrainian Thoughts and Feelings based on One Year War Content Analysis

In the age of remarkable technological innovations such as AI, quantum computing, IoT, and blockchain, one could argue that the world is becoming an increasingly connected, advanced, enlightened, and peaceful place. Nevertheless, paradoxically, conflicts and wars are still born deeply rooted in complex strategic, historical, and economic dynamics, and continue to arise finding a direct representation in both physical and digital battlefields through powerful and dynamic environments like social media. This environment enabled unprecedented connectivity and ideas, thoughts, ideologies, and experiences exchange shaping the narrative, amplifying ideas, feelings, and experiences while directly addressing the underlying causes, dynamics, and implications of conflicts and war through a multifaceted and multi-nuanced approach. The outbreak and ongoing war in Ukraine took the international community off guard representing a significant turning point in the contemporary era that received immediately intensive global attention, united global humanitarian, and strategic efforts to support and help the ones in need, and reflected its geopolitical and economic global complexities, dynamics, and implications. At the same time, a high degree of disinformation and misinformation exists surrounding different aspects about this war e.g., actions taken, and impact produced on civilians, which contributes to creating an altered perspective of reality. While different conventional media and social media outlets together with research, governmental, and practitioner efforts revealed and reflected on the nature, major incidents, and their known impact on civilians and civilian objects as well as military personnel and military objects, yet limited attention and a lower voice is given through dedicated studies to thoughts and emotions of Ukrainian users in unconventional social media platforms like Telegram. This represents the knowledge gap tackled in this research by building a set of Machine Learning-based solutions for analysing the discourses and sentiments of Ukrainian users using the Design Science Research methodology in a Data Science research approach. From this analysis, reflection is provided to important days and incidents experienced by Ukrainian population since February 2022 in the first year of war.

Enhancing User Experience Using a Framework Integrating Emotion Recognition and Eye-Tracking

In a rapidly evolving digital landscape, ensuring a seamless and engaging user experience (UX) has become paramount. This study delves into the intricate realm of web interaction design, aiming to enhance user satisfaction and engagement. Through the integration of emotion recognition and eye-tracking technologies, a profound relationship between user emotions and web interface design is unveiled. The central theme of this research revolves around the integration of emotion recognition and eye-tracking technologies to evaluate web interaction designs. An experimental study involving 24 participants from diverse backgrounds and age groups was conducted. These participants navigated web interfaces that featured both emotion recognition and eye-tracking technologies. Three distinct tasks were carefully crafted to represent a spectrum of web interactions, ranging from basic navigation to complex decision-making. Data collection involved real-time valence and arousal scores, video recordings, visual attention patterns, task completion times, and questionnaires. The analysis revealed a series of significant discoveries. Users who engaged with simplified web versions consistently exhibited elevated valence values, indicative of heightened positive emotional feedback, diverging starkly from their counterparts navigating complex web iterations. The dynamic ebb and flow of emotional states, underscored by arousal levels, underscore the pivotal role of real-time emotional assessment in the critical evaluation of web interfaces. Moreover, the study unveiled a persistent preference for a state of emotional calmness during interactions, demonstrating a universal need for user-centered design principles that prioritize minimal cognitive load and emotional tranquility. In summation, this research contributes a robust framework to the design community and academia for the comprehensive evaluation of web interaction designs. The findings underscore the paramount significance of simplicity, real-time emotional evaluation, and unwavering adherence to user-centered design principles in the realm of web interaction. This study constitutes an invaluable repository for designers, developers, and researchers, steering their endeavors towards the relentless pursuit of optimized user experiences within the ever-evolving digital landscape.

The Application and Implications of Fear Appeals in Short Videos for Beauty E-commerce

Short video advertising in e-commerce is rapidly gaining popularity, especially in the beauty industry. Many video creators rely on experience and intuition to strategically evoke user emotions in order to achieve effective marketing. This paper, framed within the theory of fear appeals, aims to explore the application of fear emotions in short videos for beauty e-commerce. It seeks to elucidate the inherent marketing logic of such videos and analyzes six commonly used forms of fear appeals from the perspective of video content composition. The study reveals that fear close-ups and the use of fear-inducing language are the most frequently employed techniques in this genre.

The FIFTH WALL. On DIGITAL PERFORMANCE between USER EXPERIENCE DESIGN and the METAVERSE

Before and since the pandemic, online virtual environments have emerged as critical sites for social and cultural experiences, facilitating conversations, creative projects, collective endeavours, and commercial exchanges. The rise of the Metaverse (Ball, 2021) represents a fundamental shift in today's digital presence. After Eva and Franco Mattes' historical happenings in Second Life, some recent hypermedia performances force a re-evaluation of the nature of performance, with a recontextualisation of the notions of reality, presence, community, and simulation. UX design reshapes and situates the emergence of 'metaverse-native' art in adjacent fields such as online 3D collaboration platforms: actual and perfect virtual stages.  Since the mid-1990s, the user has increasingly been invited to live an unusual experience in which the physical and the digital merge. The noun 'user experience' refers to how people experience the encounter with a system. It extends traditional human-computer interaction design by addressing all aspects of the product or service as perceived by the user, increasing satisfaction and loyalty by improving usability. The UX classification system is based on the user's emotions, preferences, attitudes, and emotional responses (Hussain et al., 2021). Its dramaturgical importance in an online digital performance has yet to be recognised.  This article proposes the analysis of three examples of digital performances (Dixon, 2007), in virtual 3D online environments, following the philosophy of User Experience Design, focusing on the perspectives and productions of Italian artists.Before and since the pandemic, online virtual environments have emerged as critical sites for social and cultural experiences, facilitating conversations, creative projects, collective endeavours, and commercial exchanges. The rise of the Metaverse (Ball, 2021) represents a fundamental shift in today's digital presence. After Eva and Franco Mattes' historical happenings in Second Life, some recent hypermedia performances force a re-evaluation of the nature of performance, with a recontextualisation of the notions of reality, presence, community, and simulation. UX design reshapes and situates the emergence of 'metaverse-native' art in adjacent fields such as online 3D collaboration platforms: actual and perfect virtual stages.  Since the mid-1990s, the user has increasingly been invited to live an unusual experience in which the physical and the digital merge. The noun 'user experience' refers to how people experience the encounter with a system. It extends traditional human-computer interaction design by addressing all aspects of the product or service as perceived by the user, increasing satisfaction and loyalty by improving usability. The UX classification system is based on the user's emotions, preferences, attitudes, and emotional responses (Hussain et al., 2021). Its dramaturgical importance in an online digital performance has yet to be recognised.  This article proposes the analysis of three examples of digital performances (Dixon, 2007), in virtual 3D online environments, following the philosophy of User Experience Design, focusing on the perspectives and productions of Italian artists.

Human-computer interaction: Evaluation of trust and emotional

With the advancement of information technology, human-computer interaction is becoming increasingly intelligent. This progress has led to the transformation of the car cabin from a simple driving space to an intelligent mobile life terminal. At the same time, more and more people have psychological problems in modern society, and timely adjustment of their negative emotions is of great practical significance to social harmony and stability. Traditional methods of emotion regulation require a lot of manpower and energy. Hence, this paper presents an approach that utilizes text dialogue and somatosensory interaction to detect the users emotions and subsequently adjust them. By examining and analyzing the current research landscape, the objective of this study is to offer insights for designing trustworthy and emotionally-responsive interactions in the automotive context. It can bring a better driving experience to smart car users and bring benefits to many companies. It is of great scientific and application value to carry out this research in depth to promote the development of human-computer interaction. Through literature review, case study, theoretical analysis and other research methods. This paper sorts out the establishment of trust degree and recognition of emotional changes in human-computer interaction, and puts forward the role, defects and improvements of trust establishment in human-car cooperation, as well as the reasons affecting user emotions, and how to improve the defects of the application of voice emotion recognition. It also discusses difficulties in establishing trust and misperception of emotions.

Sustainable Emotional Design Based on Industry 4.0 for Industrial Nougat Packaging

Nowadays, digitalisation is present in all links of the product life cycle and within product design. Packaging is a critical element that affects the customer’s purchase intention. Therefore, packaging is one of the elements for which it is positive to include techniques and methods based on Industry 4.0 to obtain results from users and bring them closer to the process. The relationship between packaging and the expected quality and emotions of users is a topic that is addressed in the social axis of sustainability and involves an effort to strengthen the relationship with the user. This article studies the expected quality of nougat in terms of packaging shape and colour using ANOVA analysis. For this purpose, a survey was carried out among 122 participants in Spain and Mexico. The main conclusion is that packaging with a combination of three shapes (rectangle, square and triangle) and colours (yellow, orange and red) enhances consumers’ emotions of Admiration, Satisfaction, Pleasant Surprise, Attraction, Fascination and Joy.

Music Recommendation System based on Emotions in User’s Social Media behaviour

The modern lifestyle makes people more competitive. It can lead to more stressful situations in our lifestyle. With the changes in human emotional behaviour, they tend to share their feelings on social media platforms rather than communicating with relatives. Studies proved that people used to listen to music to avoid emotional situations in their life. But there is no proper way to get the most accurate music to listen to and avoid emotional conflicts. Resolving these conflicts, the music recommendation system based on emotion introduced. It analyses the users’ recent social media content and detects the various kind of emotions. The lyrics analysing was done using natural language processing techniques to identify the music emotions. Most people pay attention to the meaning of the songs, that was the major reason to consider the emotions of the lyrics. The research was considered on a language-independent platform for both English and Sinhala.

A pilot study of measuring emotional response and perception of LLM-generated questionnaire and human-generated questionnaires

The advent of ChatGPT has sparked a heated debate surrounding natural language processing technology and AI-powered chatbots, leading to extensive research and applications across various disciplines. This pilot study aims to investigate the impact of ChatGPT on users' experiences by administering two distinct questionnaires, one generated by humans and the other by ChatGPT, along with an Emotion Detecting Model. A total of 14 participants (7 female and 7 male) aged between 18 and 35 years were recruited, resulting in the collection of 8672 ChatGPT-associated data points and 8797 human-associated data points. Data analysis was conducted using Analysis of Variance (ANOVA). The results indicate that the utilization of ChatGPT enhances participants' happiness levels and reduces their sadness levels. While no significant gender influences were observed, variations were found about specific emotions. It is important to note that the limited sample size, narrow age range, and potential cultural impacts restrict the generalizability of the findings to a broader population. Future research directions should explore the impact of incorporating additional language models or chatbots on user emotions, particularly among specific age groups such as older individuals and teenagers. As one of the pioneering works evaluating the human perception of ChatGPT text and communication, it is noteworthy that ChatGPT received positive evaluations and demonstrated effectiveness in generating extensive questionnaires.

Conditioned Canine Cadavers for Near-Natural Interprofessional Veterinary and Human Surgery Training.

Both medical and veterinary students find that the use of cadavers is critical to learning anatomical structures and surgical techniques. The use of human cadavers and the resulting user emotions are driven by serious ethical issues that are currently much less pronounced in veterinary education. Ethically sourced canine cadavers, thus, are more readily available. Aesthetics such as odor and visual appearance, though, influence both learner and educator motivation.We have investigated a way of delaying cadaver decomposition by post-mortem in situ, chemical-free, gastrointestinal lavage.We are convinced that canine cadavers, conditioned as described here, will improve the outcome of cadaver-based surgical skills training by facilitating preparation, reducing the number of required cadavers, postponing decomposition, improving the surgeon's haptic-tactile response to organ and tissue handling and suturing, and, possibly most importantly, increasing learners' and educators' focus due to the significantly improved aesthetics. We hypothesize that skill transfer for medical students and doctors, because of the similar abdominal anatomy, may be easier when training with conditioned canine cadavers as compared to artificial simulators or pigs in vivo.

Eliciting and modeling emotional requirements: a systematic mapping review.

Considering users' emotions plays an extremely crucial role in the adoption and acceptance of recent technology by the end user. User emotions can also help to identify unknown requirements, saving resources that would otherwise be wasted if discovered later. However, eliciting and modeling users' emotional requirements in software engineering is still an open research area. This systematic mapping review analyzes emotional requirements (ER) practices in software engineering from two perspectives: elicitation and modeling. For elicitation techniques, we investigate the techniques, evaluation methods, limitations, and application domains. For modeling techniques, we examine the modeling languages, analyses, limitations, and domains. We systematically reviewed studies on emotional requirements engineering published between 1993-2023 and identified 46 relevant primary studies. A total of 34 studies investigated ER elicitation techniques, five examined modeling techniques, and seven covered both. Illustrative case studies were the main evaluation method for proposed elicitation techniques. Identified limitations include time consumption and extensive human involvement. The dominant application domains were healthcare and well-being, and game development. This review summarizes the current landscape of emotional requirements research, highlighting key elicitation and modeling techniques, evaluations, limitations, and domains. Further research can build on these findings to advance emotional requirements practices in software engineering. Future research may address (1) managing conflicting emotional requirements across users, (2) evaluating the value and impact of considering emotional requirements during the development and (3) Modeling and analyzing emotional requirements in relation to other requirements.

The conceptualization of enablers and constraints of in‐store buying as part of the affordances flow funnel process through scan and go apps

AbstractThis study explores the affordances of “scan and go” apps and their influence on the flow experience of retail customers to provide a unique insight into user–technology interaction. Through a constructivist ethnographic approach, the research examines how users' socially constructed perceptions and interpretations shape these interactions, and it emphasizes the role of the material and social environment. The research innovatively conceptualizes affordances as a flow process; it introduces an affordances flow funnel that encompasses three distinct stages: perceived affordances, actualized affordances, and affordance dichotomy. By following this process, the study improves understanding of user emotions and behaviors that range from apathy to excitement, from gratification to provocation, and from abandonment to absorption. Findings underline the importance of equipping users with support to navigate technological and environmental constraints, thereby ensuring successful affordance actualization. The research contributes to the literature by revealing a new affordance type, namely affordance dichotomy, and offers valuable insights for marketers and developers to enhance user experiences and absorption behavior. Recognizing its focus on scan and go apps within supermarket contexts, the study invites future research to extend this understanding to different contexts and technologies.