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Food recommender systems have been developed for the online environment to support shoppers in making informed decisions. These systems analyze the extensive data collected to infer consumer preferences and needs, providing relevant product recommendations accordingly. Despite the potential of recommender systems as a strategic marketing tool in the online grocery shopping environment, there has been limited effort to systematically analyze approaches of prior studies on recommender systems for online grocery shoppers along the five stages of recommendation delivery: (1) identify recommendation goal, (2) acquire consumer data, (3) compute, (4) evaluate, and (5) present the recommendation. Therefore, this paper examines the advancements in each stage of delivering grocery recommendations to consumers from 2018 to March 2023. We performed a search strategy resulting in 50 papers dedicated to recommender systems for online grocery shoppers, which contrasts with previous research that typically examined recipe and meal recommendations that were merely meant to inspire users on what to cook. Findings reveal a prevalence of preference-based systems with limited integration of explicit consumer data, and often lacking consent for implicit data usage. While advanced deep neural network models are getting more attention in the literature, evaluation methods tend to be system-oriented, overlooking essential user feedback and the efficacy of general metrics. This systematic literature review underscores the necessity for consumer engagement in system and interface design, aiming for grocery recommendation systems that improve customer experience, by ensuring inclusivity and prioritizing user-centered design. [Display omitted] • Grocery recommendations usually disregard the potential of diverse objectives. • Typically no integration of explicit data and no mention of consumer consent. • There is an increasing focus on more advanced deep neural network based models. • Evaluation is typically system-centric, ignoring the more general metrics. • Systematic input from consumers is mostly absent in design and evaluation. [ABSTRACT FROM AUTHOR]

With the progress of the times and the improvement of science and technique, network message technique has occupied a vital position in people's lives. At the same time, society has been implementing university English education reform in recent years, and the "internet plus" wisdom education model is the product of the improvement of the times. This new education model has gradually integrated into the education of various subjects. Introducing the concept of message technique and wisdom education into university translation education can innovate education mode, optimize education content, and integrate high-quality education resources. Cultivating applied translators has become the trend of educational reform. Based on deep learning, this paper studies translation education skills in universities. In-depth education enables learners to acquire systematic knowledge, critical spirit, creative thinking, etc. This kind of learning fully taps individual potential to cultivate a complete personality. According to the research in this paper, wisdom education is 12% better than traditional education, and it is suitable to be widely put into practice. • This new education model has gradually integrated into the education of various subjects. • Enhancing university translation education with message technique and wisdom education modernize educational approach. • Cultivating applied translators has become the trend of educational reform. • Based on deep learning, this paper studies university translation education skills. [ABSTRACT FROM AUTHOR]

Interactive teaching is very popular in the field of education, especially in college preschool education teaching. In this study, the experimental performance of the evaluation system based on scientific emotion construction is analyzed by the machine learning algorithm. The experimental results show that the classification model realized by the machine learning algorithm is feasible and effective for the construction of an interactive design teaching evaluation system of preschool education in colleges and universities. The main research content of this experiment is for the teaching evaluation text, this paper intends to use NB, KNN, LR, and SVM algorithms as the meta-learning algorithm in the framework, the classification effect of the meta-classifier is ranked as SVM > LR > KNN > NB. From the above data comparison, the SVM meta-classifier in the algorithm in this paper has achieved the best classification effect. The SVM meta-classifier based on the algorithm in this paper performs well, and the classification accuracy rate reaches 92.1%. This shows that this model is very suitable for studying the. And the classification accuracy rate reaches 92.1%. This shows that this model is very suitable for studying the construction of interactive teaching evaluation systems under emotional education. • The experimental results show that the classification model realized by machine learning algorithm. • This shows that this model is very suitable for studying the construction of interactive teaching. • The main research content of this experiment is for the teaching evaluation text. • This paper intends to use NB, KNN, LR and SVM algorithms as the meta-learning algorithm. [ABSTRACT FROM AUTHOR]

As many services convert to digital based on human-machine communication technology, older adults face considerable challenges. With the goal to identify ways to design digital services that are easier for older adults to use, this paper uses the strategy of making self-ordering kiosks more similar to the original version (i.e., paper menu) focusing on three familiarity design approaches: representation, manipulation, and organization. A 2 (skeuomorphic vs. flat design) x 2 (hierarchical vs. linear navigation structure) between-subject design experiment was conducted with individuals aged over 65 years (N = 60). Participants perceived that the skeuomorphic design was easier to use compared to the flat design, and the linear navigation structure increased perceived self-efficacy, usefulness, and intention to use compared to the hierarchical navigation structure. Participants also completed the tasks more quickly in the skeuomorphic design (vs. flat design) and linear navigation structure (vs. hierarchical structure) conditions. Interaction effects suggest that the task completion time was further reduced when skeuomorphic design was used with a linear navigation structure. Furthermore, fewer people requested assistance when they used a linear navigation structure. Serial multiple mediation results showed that the influence of linear navigation structure on intention to use was mediated by perceived self-efficacy and usefulness. • Skeuomorphic design offers better user experience for seniors than the flat one. • Linear navigation structure offers better user experience for seniors than the hierarchical one. • Combining skeuomorphism and linear structure decreases the task completion time. • The effect of linear navigation structure on intention to use is mediated by self-efficacy and perceived usefulness. [ABSTRACT FROM AUTHOR]

At present, ubiquitous learning has been becoming an important learning style for college students. However, the current studies on ubiquitous learning mostly focus on aspects such as communication and data interaction methods, while ignoring students' academic emotions. In this paper, we propose an individual adaptive ubiquitous learning paradigm that focuses on college students' academic emotions. The paradigm collects and analyses students' academic emotions to grasp student's individual characteristics. Then, the adaptive planning and adjusting learning contents is beneficial for improving students' academic emotions and enhancing the ubiquitous learning effects, initiative and concentration. In this study, the 2-year-long comparative experiments and tracking analyses were conducted from four aspects: academic grades, average study hours in after-school spare time, academic emotions status and classroom participation. The experimental results show that the individual adaptive ubiquitous learning paradigm proposed in this paper has significant positive effects and impacts on college students' learning outcomes, initiative, engagement and academic emotions. • An individual adaptive ubiquitous learning paradigm considering the impact of academic emotions is proposed. • The paradigm focuses on academic emotions to adaptively adjust individual learning content. • Academic emotions analysis and adjustment algorithms are designed to improve learning outcomes. [ABSTRACT FROM AUTHOR]

This paper delves into the realm of virtual assistants (VAs) and their pivotal role in shaping user acceptance of voice shopping. VAs, initially tailored for voice interactions on smartphones, have permeated diverse consumer devices, revolutionizing user experience through conversational interfaces. However, the reluctance to embrace voice shopping persists due to safety apprehensions stemming from users' lack of confidence in VAs. The paper centers on anthropomorphism, emphasizing the human-like attributes of VAs, and its direct correlation with users' sense of safety. The study explores user perceptions of VAs in voice shopping, particularly focusing on anthropomorphic aspects like social presence, human-like voice, and friendliness. The investigation highlights their impact on perceived safety, word-of-mouth, and voice shopping acceptance. Analyzing prominent VAs—Alexa, Google Home, and Siri—the study identifies two fundamental factors influencing voice shopping acceptance: the humanity embedded in the VA's voice and the perceived safety it offers. Feeling secure during VA interactions significantly increases safety perception, fostering greater acceptance of VAs for shopping purposes. Additionally, the human-like qualities in the VA's voice positively influence users' perceived friendliness and safety, augmenting trust and overall acceptance of this technology. • The humanization of virtual assistants enables the generation of user confidence. • Perceived security in these assistants promotes active word-of-mouth transmission. • Perceived security enhances the intention to engage in voice shopping using virtual assistants. • The perceived humanity is manifested through the interplay of human-like voice, social presence, and friendliness. [ABSTRACT FROM AUTHOR]

The increasing usage of social media networks has raised concerns about the growing frequency of cyberbullying incidents. The definition of cyberbullying lacks universal consensus, yet according to several authors, cyberbullying is characterized by aggressive, repetitive, and intentional communication among peers. However, existing cyberbullying detection datasets often focus solely on classifying texts as aggressive or non-aggressive, neglecting the other cyberbullying aspects, thus hindering research progress. This paper proposes a framework for designing a new dataset incorporating all four aspects of cyberbullying to address this gap. The text messages are sourced from a real dataset, while the users' data is generated synthetically. The resulting dataset contains messages exchanged randomly among different pairs of users, thus inculcating repetition. Additionally, the degree of peerness, defined and calculated to measure the likelihood of two users being peers, is used. The intent of harm is quantified as a numeric value using the ratios of aggression and repetition. As a result, the proposed dataset encompasses all four aspects of cyberbullying by providing repeated aggressive messages among users along with quantitative values of the degree of peerness and intent to harm. The proposed dataset is adaptable, with adjustable threshold values for peerness, repetition, and intent to harm, offering flexibility for various applications. The paper concludes by presenting the results of some baseline machine-learning methods on the proposed dataset. • Generation of a semi-synthetic dataset for automatic cyberbullying detection. • The dataset includes all aspects of cyberbullying: aggression, repetition, intent to harm, and occurrence among peers. • Presentation of baseline results on the proposed dataset. [ABSTRACT FROM AUTHOR]

Numerous studies have examined the utility of virtual reality (VR) technologies in the transportation and logistics sector. However, no systematic and comprehensive review of this research area has been performed. This need is addressed in this paper by reviewing publications on the development and applications of VR technologies in the four main categories of transportation and logistics: air, maritime, railway, and road. A clustering analysis of 200 papers on VR in transport and logistics published from 2010 to 2023 has been performed. It identifies six clusters of research: operator training in routine procedures, operator training in incident handling, simulation of carriers, design of traffic infrastructure and carriers, psychological studies on transportation and logistics operators or associated parties, and treatment of illness related to transportation and logistics. Based on the review and the clustering analysis, the paper proposes directions for future research on the development of VR and its applications in transportation and logistics. • A review of 200 peer-reviewed VR papers published from 2010 to 2023 is conducted. • The papers are from 4 main categories of logistics: air, marine, railway and road. • Six clusters of research are identified from a clustering analysis of the papers. • Directions for future VR research in transportation and logistics are proposed. [ABSTRACT FROM AUTHOR]

Social networking sites (SNSs) provide users with ample opportunities to share their own information and participate in social browsing to get to know others. Drawing upon signaling theory, this paper investigated how and to what extent recommendation letters' content information (breadth and depth) and external information (field and relationship) affect career mobility. Based on the open data from LinkedIn, this paper adopted the Latent Dirichlet Allocation (LDA) method to capture the breadth and depth of the recommendation letter, and used elaboration likelihood model to test our model. The results show that both content information and external information of the recommendation letter have significant positive impacts on the career mobility. In addition, the social network size shown converse moderating effects between recommendation letter content information and career mobility. This paper extends the boundaries of signaling theory by creatively using machine learning methods to measure textual signals (i.e., recommendation letter). The research results provide practical implications for personal career development and firm talent management. • The central and peripheral information of recommendation letter are positively related to career mobility. • Social network size has converse moderating effects on central information of recommendation letter and career mobility. • Machine learning method to measure the breadth and depth of recommendation letter. [ABSTRACT FROM AUTHOR]

Although the metaverse is still in the early stages of development and implementation, it has the potential to revolutionize the way how businesses can interact with customers through both the virtual and real world. In particular, service industries are already exploring the opportunity to utilize the metaverse to provide more immersive, interactive and engaging customer experiences. However, the holistic overview of the future applications, opportunities, and challenges of a metaverse in the context of service industries from academic and expert perspectives is limited. By employing a multi-perspective approach, this study looks into these unexplored aspects of the metaverse in the context of service industries through informed and multifaceted narratives by leading academics and experts from cross-disciplinary backgrounds from media and communication, education, hospitality, financial services, retail, tourism and healthcare. The main opportunities identified include the development of new experiences, the introduction of novel inter-world interactions, and new business-consumer relations within the metaverse. The key challenges covered include current technological boundaries, limitations of the experiences in the metaverse, health issues, and data privacy, security, and legal issues. The paper concludes with formulating future research agendas and presenting contributions to literature and implications for practice. • It explores future applications, opportunities, challenges, and research agenda of the metaverse in service industries. • Opportunities include new experiences development, novel inter-world interactions, and new business-consumer relations. • Key Challenges are technological boundaries, limited experiences, health, data privacy, security, and legal issues. • The paper concludes with formulating future research agendas and presenting contributions to literature and practice. [ABSTRACT FROM AUTHOR]

The buyer-seller relationship in live streaming commerce is crucial especially in service failure situations, yet it has been underexplored. In this paper, we reconceptualized the relationship between consumers and sellers in live streaming commerce as "parasocial guanxi", which consists of ganqing (emotional attachment), xinren (trust) and reciprocal value. The effects of parasocial guanxi on consumer dissatisfaction and complaint intention in service failure situations were further investigated based on the expectation confirmation theory. Our study involved 425 valid questionnaires and employed the partial least squares structural equation method (PLS-SEM). The findings are mixed: on one side, parasocial guanxi acts as a buffer, mitigating dissatisfaction and complaint intention in the face of product or service problems and reducing the impact of disconfirmation on consumer dissatisfaction. On the other side, it may also increase the likelihood of dissatisfied consumers complaining. Furthermore, the buffering effect weakens as consumers make more frequent purchases. The findings have important theoretical and practical implications for understanding the buyer-seller relationship in live streaming commerce. • This paper reconceptualized the buyer-seller relationship in live streaming commerce as "parasocial guanxi". • The effects of parasocial guanxi in service failure situations were investigated. • Parasocial guanxi has a buffering effect in alleviating consumers' dissatisfaction and complaint intention. • Meanwhile, parasocial guanxi can increase the likelihood of dissatisfied consumers to complain. • The effects of parasocial guanxi vary across different demographic groups. [ABSTRACT FROM AUTHOR]

In order to fully understand the overall evaluations and sentiments of green products by the Chinese public, and comprehensively enhance the public's awareness of green consumption, this paper conducts sentiment analysis and text mining based on 85306 online reviews of 8 typical green products in four major fields of China's JingDong (JD.com) e-commerce platform, including organic food, daily cleaning, green building materials, and energy-saving home appliances. Research has found that: (1) The consumers' preferences and attentions to different attributes of green products vary depending on the product; (2) The public's overall evaluations and satisfactions with existing products are relatively high; (3) Found 9 topics related to consumers' positive sentiments (i.e., enthusiastic service, beautiful appearance, good taste, good quality, favorable price, trustworthy brand, powerful function and effect, fast logistics and delivery, high-cost performance) and 3 topics related to negative sentiments (i.e., poor service attitude, smelly, and noise); (4) Consumers' attentions, positive and negative sentiments for most of the attributes of this green product show an upward trend to varying degrees. The results of this paper provide reliable practical evidence for the promotion and use of green products, which is of great significance for promoting green consumption. • The paper established an online reviews analysis framework for green production. • We explored consumers' overall evaluations and sentiments towards green products. • We have found 9 topics to consumers' positive sentiments and 3 topics to negative. • Consumers' preferences for green attributes vary depending on the products. • Helping to enrich the sources and acquisition methods of green consumption data. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is playing an important role in the development of cars, smart homes and schools. Schools are using IoT technology to enhance student learning, digitize traditional learning and improve academic performance. IoT is rapidly replacing the traditional school system with a modern, smart and safe school system. Several modern education systems are presented in the literature. The difficulty of choosing a smart and safe school system while evaluating the respective merits of different school systems has long been a concern for educators. In this study we proposed a hybrid multi-criteria decision-making method (MCDM) to address the selection Problem. To rank the different smart school systems and evaluate the value of the required parameter, two MCDM-based methods are used: Entropy and TOPSIS (Technique for Preference Ordering by Similarity to an Ideal Solution). Twelve beneficial features were considered that represent the fundamental positive characteristics required to create an intelligent education system. Ten different educational systems are considered as alternatives in order to carry out an evaluation. Entropy is used to measure the importance of each criterion and TOPSIS is used to rank the school systems. In this paper, we propose how the concepts of Entropy and TOPSIS can be used to address the challenge of selecting a safe and smart school system based on IoT. Our investigation selected the IoT-based school system that was found to be the smartest and safest out of a set of schools. Finally, we discuss the evaluation of the proposed research. • Review IoT applications in education and transform traditional schools into smart, secure systems. • Apply hybrid techniques to select a smart and secure school system. • Determine key components of IoT-based school systems via literature analysis. • Use entropy to measure criteria importance and TOPSIS for ranking alternatives. • Identify and prioritize a smart, secure school system in this research. [ABSTRACT FROM AUTHOR]

To address the challenges of an increasingly remote workforce, there is an urgent need for organizations to understand the precursors and consequences of workplace cyber mistreatment. The present systematic review consolidates the empirical research on workplace cyber mistreatment with the goals of a) providing a cohesive term and definition for cyber mistreatment; b) estimating the magnitude and direction of associations within cyber mistreatment's nomological network; and c) exploring the relative importance of cyber and face-to-face (F2F) mistreatment in predicting employee outcomes. Utilizing a systematic search of databases, conference proceedings, and references of relevant papers in September 2023, we identified and independently double-coded 43 samples (N = 19,642) of working adults that reported experienced cyber mistreatment at the individual level. The results of random-effects psychometric meta-analyses identified numerous antecedents of cyber mistreatment, including age, gender, neuroticism, support, and work demands, among others. Furthermore, cyber mistreatment predicted both employee behaviors and well-being outcomes, including deviance, F2F mistreatment, burnout, and job satisfaction, among others. Lastly, the results of relative weights analyses were largely counter to expectations in that F2F mistreatment typically accounted for more explained variance than cyber mistreatment. Some limitations include the strong correlation between cyber and F2F mistreatment and the inability to assess many contextual factors. The current research not only provides construct clarity about cyber mistreatment, but also enhances our understanding of the nomological network of this construct, thereby informing future research and interventions geared towards mitigating cyber mistreatment. • Consolidated terms and definitions of cyber mistreatment at work. • Meta-analytically identified magnitude and direction of associations with cyber mistreatment. • Unexpectedly, face-to-face mistreatment was typically a stronger predictor than cyber mistreatment. • Measures of cyber and face-to-face mistreatment were strongly related. [ABSTRACT FROM AUTHOR]

Traditional teaching methods have been bolstered by modern teaching methods and multimedia technology, allowing students to benefit from both new and old approaches to learning. Teaching and learning are evolving at an unprecedented rate because of the rise of online courses. Rapid advances in intelligent technologies and communication networks provide new opportunities for interactive technology innovation and technical support for hybrid teaching incorporating both on- and offline study. For this article to be helpful, it needs to examine how an intelligent mobile communication network's effective teaching combined with a hybrid teaching mode can improve the educational attainment of student teachers' English reading, among other things. This article should address these issues and more. According to this paper's findings from the experimental study, college students' desire for and capacity to learn independently in English reading courses has increased massively, and our English reading results will rise by at least 93%. • Teaching and learning are evolving at an unprecedented rate because to the rise of online courses. • On the basis of mastery of observational learning and constructivist teaching theory. • There is no longer a restriction on the amount of time or place in which individuals may communicate. • No longer any concerns regarding short-term single network lines thanks to the advent of mobile devices. [ABSTRACT FROM AUTHOR]

Direct-to-Avatar (D2A) is the new phenomenon in the online retail segment. Brands are moving towards immersive commerce in which the central focus is on immersive communication for better customer experience in the metaverse. Diffusion of innovation theory acted as a theoretical framework to understand the premiums that the brands can enjoy from the customers by moving towards immersive commerce. 948 tweets on metaverse were analysed and five in-depth interviews with the experts on metaverse were conducted. For the quantitative study, the data were collected from a select metaverse Facebook group. The findings of PLS-SEM revealed that four factors - customer engagement, customer experience, value co-creation and customer empowerment - have statistically positive impact on customer citizenship behavior which ultimately affects customer satisfaction and loyalty towards the brands. The study extends the applications of diffusion of innovation theory in the content of immersive communication. It enriches the literature on technological advancements in immersive commerce. This is one of the first studies that focus on lifestyle brands in the metaverse. Also, this study depicts how socializing the digital brand communication with experience economy can be a key factor for lifestyle brands. • This paper is one of the first that focuses on lifestyle brands in the metaverse. • This study depicts how socializing the digital brand communication with experience economy is crucial for lifestyle brands. • The study extends the applications of diffusion of innovation theory in the content of immersive communication. • It enriches the literature on technological advancements in immersive commerce. • Customer engagement, experience, co-creation and empowerment effects citizenship behavior boosting satisfaction & loyalty. [ABSTRACT FROM AUTHOR]

Despite assumptions that wearable self-care technologies such as smart wristbands and smart watches help users to monitor and self-manage health in daily life, adherence rates are often quite low. In an effort to better understand what determines adherence to wearable self-care technologies, researchers have started to consider the extent to which a technology is perceived as being part of the user (i.e., technology embodiment) and the extent to which users feel they can influence reaching their health goals (i.e., empowerment). Although both concepts are assumed to determine adherence, few studies have empirically validated their influence. Furthermore, the relationships between technology embodiment, empowerment, and adherence to wearable self-care technology have also not been addressed. Drawing upon embodied theory and embodiment cognition theory, this research paper introduces and empirically validates 'embodied empowerment' as a predictor of adherence to wearable self-care technology. Using partial least squares structural equation modeling and multigroup analysis on a dataset of 317 wearable self-care technology users, we find empirical evidence of the validity of embodied empowerment as a determinant of adherence. We also discuss the implications for research and practice. • We introduce embodied empowerment to explain adherence to self-care wearables. • Embodiment and empowerment reinforce each other and function in conjunction. • Embodied and empowerment predict adherence to wearable self-care technology. • The results are consistent for male versus female and younger versus older users. [ABSTRACT FROM AUTHOR]

Non-fungible tokens (NFTs) represent a multibillion-dollar global market. While considerable speculation exists about the future utility of NFTs, there has been limited research into the consumer behaviors of market participants. This research paper examines the motivations of NFT buyers through the lens of self-determination theory. Using a sample of 482 participants, the authors tested a conceptual framework to better understand both NFT buyers' intrinsic and extrinsic motivations. This study expands the literature on NFTs in three different ways: i) it is the first study, as far as we know, to focus exclusively on NFT buyers and their motivations in purchasing NFTs; ii) it explores a variety of potential motivations theorized in the literature; and iii) it tests the expected future value of NFTs as both a motivation and as a moderator for NFT buyers. The authors determined that intrinsic motivation had the most substantial effect on purchase intention, and the expectations of NFTs' future value positively moderated the effect of amotivation on purchase intention. In contrast, high expectations of future value moderated the effect of external regulation on purchase intention. The results suggest that NFT buyers are not as impacted by potential social or monetary gain as often characterized in the academic literature but behave more like traditional buyers of luxury goods. • Seminal study on motivations behind NFT buyers' decisions to purchase NFTs (n = 486) • Used SIMS to test a variety of motivation effects (intrinsic, extrinsic, amotivation) • Intrinsic motivation had the most substantial effect, contradicting a common narrative of NFT buyers • Buyers' expectation of future value acts simultaneously as a determinant and moderation effect in the purchase of NFTs • NFTs should be considered a novel form of luxury goods [ABSTRACT FROM AUTHOR]

Digital presence is increasing on social platforms, and increasing numbers of companies have begun to invite virtual influencers to endorse their products. However, the question of whether AI endorsers can completely replace real humans is a challenging one. Therefore, in this study, we attempt to identify the differences in consumer purchase intention between consumers of products promoted by AI endorsers versus real human endorsers. In two studies, we found that AI endorsers effectively stimulated consumers' purchase intentions when recommending search products. For experience products, the marketing effect of a real human celebrity endorser is better, however, and consumers' purchase intention is stronger. Perceptions of congruency mediate the interaction of endorser and product type on consumers' purchase intention; self-image congruency mediates the influence of AI endorsers on consumers' purchase intention for search products. Moreover, functional congruency mediates the influence of celebrity endorsers on consumers' purchase intention for experience products. This paper is helpful for companies to encourage them to consider the role of different product attributes and adopt more appropriate strategies to maximize the effect of endorsement marketing strategies. • This study explores the interaction between endorser and product type on purchase intention. • The research proposes the effect of self-image congruency on purchase intention. • Functional congruency mediates the influence of celebrity endorser on consumers' purchase intention. • We advise managers not to blindly follow the trend of choosing AI as endorser. [ABSTRACT FROM AUTHOR]

Criminal cases often exhibit imbalance and cannot be extended by data augmentation when classified into attribution types. To solve the problem of unbalance data in offenders' attribution classification, this paper proposes a criminal psychological attribution assessment model by an improved Balanced TF-Distinguishing IDF method (B-TF-dIDF) and constructed a hybrid network with attention method to fuse numerical and text features for improving the accuracy. First, as a statistical method, B-TF-dIDF is presented to reduce the impact of class-imbalance for extraction of numerical features, in which a balanced element is added to reduce the effects of incorrect type keywords on classification, and a distinguishing element is added to discriminate the types of keywords. Then, an improved hybrid network model composed of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) is constructed to balance the influence of different lengths of text samples for extracting the semantic features of criminal texts. For evaluating different feature weights by their importance, Spatial Attention is used to improve CNN in the feature maps. Moreover, the self-attention is also performed to re-evaluate the mixed features. Finally, the softmax classifier provides a scientific basis for developing a hierarchical treatment mechanism further. Additionally, we build a criminal data set with labels from real cases for testing. The experiment proved that the proposed model is better than other related methods in various evaluation indicators, including the micro and macro scopes. Moreover, the F1 of minority samples has increased by 6%–8%, indicating that the proposed method can reduce the impact of class-imbalance. • A hybrid model composed of LSTM and CNN is constructed to classify criminal psychology attribution into three types. • The novel statistical method B-TF-dIDF has been constructed to process unbalanced data and extract numerical features. • Text and numerical features are fused and re-evaluated by Self-attention. [ABSTRACT FROM AUTHOR]

Under the background of the COVID-19 pandemic, our paper attempts to advance a dual-process model from online social support to individual resilience via diverse social capital (bonding and bridging) and political beliefs (political efficacy, political trust and city identification). Drawing on a survey of 446 residents in Shanghai, China, the findings indicate that neither informational nor emotional social support directly affects individual resilience, but indirectly influences it through different pathways. Specifically, bridging social capital mediates informational social support and individual resilience, but bonding social capital might not follow a similar path. Notably, political efficacy and political trust are involved in the above mediation between informational social support and individual resilience. Besides, the serial mediation effect of emotional social support on individual resilience via bonding social capital and then city identification or political trust is also significant. Our findings are expected to reveal the mechanism of resilience construction and prepare for the future public health crisis. • Neither informational nor emotional social support directly predicts individual resilience in China during the COVID-19. • Bridging social capital mediates the relationship between informational support and resilience. • Political trust explains the mechanism from social support to resilience via both bonding and bridging social capital. • Political efficacy acts in the sequential mediation of informational support, bridging social capital, and resilience. • City identification acts as the pathway connecting emotional support, bonding social capital, and resilience. [ABSTRACT FROM AUTHOR]

This discussion takes a human-centred perspective of the contributions of the collection. Its papers explore diverse, new uses of AI with rich, multimedia sensor data towards new ways to measure and understand self-regulated learning. This work can contribute to the learning sciences. It can also provide a foundation for future personalised teaching and learning systems with explainable AI (XAI) and learner control. I will discuss the papers from that perspective with a focus on an important form of XAI in education – the Open Learner Models (OLM). When suitably designed, OLMs can empower a learner to: (1) contribute data about themself and their self-regulated learning processes, complementing conventional and multimedia data; (2) scrutinise and control learner data collection and use in AI-based systems and (3) be the controlling partner in AI-teaming that scaffolds their self-regulated learning processes. [ABSTRACT FROM AUTHOR]

The study does a thorough bibliometric analysis of the subject through time to analyze the research landscape of social media addiction (SMA). The study concentrated on the scientific publications' topic, research trends, and scholarly production in social media addiction. From the Scopus database, the authors retrieved 712 peer-reviewed papers. The bibliometric technique thoroughly analyzed the trend, thematic focus, and scientific output in social media addiction. The analysis propounds that significant work in the field of social media addiction kickstarted in 2010. The most pertinent publications for articles about social media addictions are "International Journal of Environment Research and Public Health," "Journal of Behavioural Addiction" and "Computers and Human behavior." Griffith et al. (2016) work is the most cited of the examined materials. And amongst the nations, the United States has contributed the most to social media addiction research and has the most extensive number of scientific papers. The results also listed the discipline's most influential academic institutions and well-known researchers. The popular accompanying fields of analysis as revealed by the word map of the keywords, include " internet addiction", "behavioural addiction", "Facebook addiction", "anxiety, and "depression". Thematic analysis suggests that researchers in this field may explore Narcissism, Psychopaths, and Machiavellianism, to provide a better perspective on social media addiction. Also, emerging themes like " Depressive symptoms, Emotional Regulation, and Social Networking Sites (SNS) Addiction " appear to be the new dimensions of social media addiction. The Bibliometric analysis helps the present study make a valuable contribution to the area by helping to provide the direction of the existing work and the future orientation required. These findings aim to aid researchers, particularly those who are just starting in the subject of social media addiction, in deciding what areas of the field to focus on for their research; what methodology has been used and most cited; where to get the work published; which dimensions to explore, and with whom to collaborate. • Social media Addiction(SMA) is being researched extensively across the globe. • There is an annual growth rate of 42.82% in the research of SMA. • The growth is exponential in the years 2020 and 2021 (due to increase in SMA during the pandemic). • The United States continues to be the nation most relevant in SMA research. • Emerging themes in the field which need focus are Depressive symptoms and Emotional Regulation. [ABSTRACT FROM AUTHOR]

Machine learning and learning analytics are powerful tools that not only support researchers in the detailed measurement and enhancement of learning processes in various learning environments, but also enable the aggregation and synthesis of evidence regarding effective educational practices. This paper describes the development and application of machine learning algorithms aimed at semi-automatic selection of abstracts for a meta-analysis on the effects of simulation-based learning in higher education. The goal was to reduce the workload while also maintaining the transparency and objectivity of the selection process. The algorithms were trained, validated, and tested on a set of 3187 studies on simulation-based learning found in medical and educational databases collected before April 2018. Subsequently, they were utilized to classify abstracts for a follow-up meta-analysis consisting of 2373 studies (published between 2018 and 2020). The aim of training the algorithms was to predict studies' abstract eligibility based on words and combinations of words used in these abstracts. The application of the algorithms reduced the number of studies that had to be manually screened from 2373 to 711. A total of 458 studies from automatically selected abstracts were included in the full-text screening, indicating the high precision of the algorithms (also compared to the performance of human raters). We conclude that machine learning algorithms can be trained and used to classify abstracts for their eligibility, significantly reducing the workload for the researchers without diminishing objectivity and quality when updating systematic literature reviews with or without a meta-analysis. • Machine learning algorithms can be used to classify abstracts for their eligibility. • Machine learning can significantly reduce the workload without compromising quality, when updating meta-analysis. • Some machine learning algorithms can outperform human raters in precision. [ABSTRACT FROM AUTHOR]

Workplace cyberbullying is a significant problem in higher education institutions. This paper examines faculty self-reports based on victimization, coping, gender, and the Big 5 Personality traits. A cross-sectional survey was distributed via Qualtrics to obtain the perceptions of 179 faculty members. Prevalence results indicated that faculty victims experienced cyberbullying from colleagues/peers, administrators, staff, students, and external members. Results also demonstrate that university faculty are unaware of resources to address cyberbullying. The study found evidence of gender differences in cyberbullying victimization in higher education. Agreeableness and neuroticism were also related to experiencing workplace cyberbullying. The article concludes with a discussion of the study's implications and potential areas of future research. • Most faculty experienced cyberbullying from colleagues/peers, administrators, and students. • Cyberbullied faculty are not likely to report the incident, which make it difficult to be addressed in the future. • Females are more likely to experience cyberbullying across relationship types in comparison to male faculty members. • The personality traits of agreeableness and neuroticism related to workplace cyberbullying. [ABSTRACT FROM AUTHOR]

Most prior work on online reviews assumes that the value of reviews for consumers lies only in providing information about the product or the consumer's experience with the product. Yet, consumers also post and interact with pseudo-reviews, defined as reviews that describe exaggerated product experiences while trying to be entertaining. To address the nature and consequences of pseudo-reviews, this study develops a framework for understanding their value and how they affect consumer decision-making. First, we define how pseudo-reviews differ from other types of reviews. Then, we empirically examine how pseudo-reviews moderate the relationship between online review valence (how positive or negative the review is) and purchase intention. Finally, using a dual-processing theoretical lens, we examine how pseudo-reviews affect consumer decision-making through systematic and affective processing. We test our model through two experiments. The first study finds that pseudo-reviews reduce the impact of review valence on purchase intention when compared to genuine reviews. The second study shows that pseudo-reviews affect uncertainty and amusement, and these, in turn, affect purchase intention. We discuss the implications of pseudo-reviews for theory and practice. • Previous studies on online reviews often ignore the amusement value of online reviews. • The paper focuses on pseudo-reviews and develops a framework to understand their influence on consumer decisions. • For positive reviews, pseudo-reviews decrease the positive effect of review valence on purchase intention. • Pseudo-reviews affect consumer decisions by increasing both uncertainty and amusement. [ABSTRACT FROM AUTHOR]

Our contemporary society demands highly qualified professionals in all sectors, and education serves as the keystone for achieving this goal. While educational institutions are diligently preparing their students to thrive in this context, emphasizing inclusivity across all demographics is crucial. An essential group in this regard comprises students with Intellectual and Developmental Disabilities (IDDs), who require tailored tasks, content, and activities to facilitate their learning. A crucial consideration is facilitating their success in education, and in this context, Learning Analytics (LA) emerges as a potential solution. LA aims to optimize students' learning experiences by gathering and analyzing their data in order to facilitate better interventions. However, it is imperative to ascertain whether LA has been effectively utilized with IDD students. To address this issue, this research project proposes a Systematic Literature Review, considering six of the most relevant scientific works sources, and identifying 364 studies. These studies underwent meticulous filtering and evaluation, resulting in 28 records which specifically address the use of LA with IDD students. Insights gained from the review indicate that the application of LA in the learning experiences of IDD students is viable. However, it necessitates careful consideration of factors such as students' difficulties and special characteristics, learning contexts, and the available resources to construct effective learning interventions. • Students with intellectual and developmental disabilities (IDD) must be included in education and require adaptivity. • Learning Analytics (LA) has proven successful in diverse contexts and it could be applied to students with IDD. • Determining LA applicability for IDD students and exploring implementation necessitate a Systematic Literature Review. • An SLR is carried out with 6 relevant sources, 364 imported and 28 selected papers that show LA application is possible. • LA facilitates the learning adaptions in activities, contents, environments and feedback for students with IDD. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the influence of various advertising channels on consumers' value perceptions of luxury brands, with a specific focus on the potential negative effects of TikTok on luxury advertising. Using an experimental design, four studies were conducted to rigorously examine these research questions. Study 1 reveals that, compared to traditional media, TikTok advertising has a more adverse impact on consumers' value perceptions of luxury brands. In Study 2, the mediating role of psychological distance is identified as the underlying mechanism explaining how media types in luxury advertising affect value perceptions. Study 3(a) highlights significant disparities in the number of online reviews and "likes" for different review types. Additionally, Study 3(b) discovers that self-deprecating online reviews can significantly increase the value perception of luxury brands on TikTok. This study contributes both theoretically and practically to the field of luxury marketing management, offering insights into the nuanced dynamics of luxury advertising across diverse media channels. Furthermore, it provides valuable suggestions for future research within the realm of luxury marketing, particularly in the context of social media. • Advertising on TikTok may diminish consumers' value perceptions of luxury brands. • Psychological distance explains TikTok's negative effects on value perception. • TikTok users prefer exploring self-deprecating reviews, when watching luxury ads. • Self-deprecating reviews enhance TikTok users' value perception of luxury brands. [ABSTRACT FROM AUTHOR]

This paper examines the use of Augmented Reality Smart Glasses (ARSGs) in order-picking tasks in warehouses and explores their impact on workers' well-being. While previous research has primarily focused on the performance advantages of ARSGs, this study provides a new perspective by investigating the human factor and perceptions of worker well-being in two empirical studies. The results corroborate previous findings that ARSGs enhance order-picking efficiency by improving workers' speed and reducing error rates. Additionally, the results reveal that using ARSGs directly increases perceptions of well-being compared to traditional support tools. However, contrary to expectations, ARSG use does not generally lead to higher job satisfaction or perceived productivity enhancements for all workers. Technology savviness is identified as a crucial individual factor that shapes these effects, with tech-savvy workers benefiting more from ARSG use. Overall, this research underscores the importance of tailoring ARSG implementation to the specific needs and characteristics of the workforce and highlights the need for further investigation into the beneficiaries of ARSG technology. • Augmented reality smart glasses (ARSGs) improve efficiency in order-picking tasks, enhancing speed and reducing error rates. • ARSG use directly increases workers' perceptions of well-being compared to traditional support tools. • This is driven by increased job satisfaction and perceived productivity, but only for workers with high technology savviness. [ABSTRACT FROM AUTHOR]

While the study of offline prosocial behavior has a long tradition, much less information is available about how these behaviors manifest and change in the digital environment, and little is known about their background. This paper evaluates differences by age and gender in a variety of attitudes and beliefs during adolescence and studies their influence on the online prosocial behavior emitted and received. A cross-sectional study was performed with 1299 participants aged between 14 and 20 from the Region of Madrid (Spain). The Spanish adaptation of the Online Prosocial Behavior Scale and a selection of items from various studies on attitudes and beliefs regarding altruism, direct and indirect reciprocity, social responsibility, and the perception of the subjective norm were administered. The results suggest that female adolescents maintain higher altruism, social responsibility, and indirect reciprocity than males, and that the older age group (18–20 years old) has higher scores in altruism, social responsibility, and direct reciprocity. Together with altruism, the subjective norm, social responsibility, and indirect reciprocity positively influence the online prosocial behavior emitted by adolescents. Indirect reciprocity, the subjective norm and altruism also influence the feeling of receiving online prosocial behaviors from others. Knowing the extent to which adolescents hold prosocial beliefs and which of these beliefs may favor prosocial online behaviors can be beneficial when promoting such beliefs and fostering more positive online conduct, as well as lessening cyberbullying, online hate and any other manifestation of aggressive behavior online. • Social networks constitute a space for the socialization of prosocial behavior in adolescence. • Beliefs about altruism, social responsibility, and indirect reciprocity favor the emission of online prosocial behavior. • Beliefs about altruism and indirect reciprocity favor greater perception of receiving prosocial behaviors online. • The prosocial subjective norm favors both the emission and reception of online prosocial behaviors. • Direct reciprocity does not seem to influence the emission and reception of online prosocial behaviors. [ABSTRACT FROM AUTHOR]

Over the last decade, Educational Data Mining (EDM) and Learning Analytics (LA) have evolved enormously as interrelated research areas and disciplines. Many researchers interested in these areas may wonder why there are two different communities, whether they are the same concept or not, and the differences between them, which is key information for designing their research and publication strategies. To address this, we conducted a systematic review of academic papers about the differences between LA and EDM following the Preferred Reporting Method for Systematic Reviews (PRISMA) guidelines. We selected 10 research works and identified 11 differences. Our conclusions are that, although both use the same data and share similar goals and interests, EDM and LA are different research communities with different origins and focuses, with their respective conferences and journals. However, there is active collaboration between the two communities and their members often tend to publish in both fields' conferences and journals. Additionally, none of the differences are apparently large enough to conclude that LA and EDM follow different paths for improving the teaching-learning process, but rather the opposite. Following a common future line, it seems that the two "sister" communities are working together with the same perspective, along with some "cousin" communities such as AIED (Artificial Intelligence in Education), L@S (Learning at Scale), Learning Science (LS), etc. in the same area that could be called Educational Data Science (EDS). We propose using the term EDS to integrate both LA and EDM with all these related communities. [Display omitted] • Educational Data Mining (EDM) and Learning Analytics (LA) are interrelated and sometimes interchanged terms. • Five original differences between EDM and LA have been identified. • Other six new differences have emerged since these initial five differences. • The term Educational Data Science (EDS) is proposed to integrate EDM and LA. [ABSTRACT FROM AUTHOR]

Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its roots in two theoretical models of the comprehension process (i.e., the Construction-Integration model and the Landscape model), and the new version leverages state-of-the-art Large Language models, more specifically ChatGPT, to have a better contextualization of the text and a simplified construction of the underlying graph model. Besides showcasing the usage of the model, the study introduces three in-depth psychological validations that argue for the model's adequacy in modeling reading comprehension. In these studies, we demonstrated that AMoC is in line with the theoretical background proposed by the Construction-Integration and Landscape models, and it is better at replicating results from previous human psychological experiments than its predecessor. Thus, AMoC v4.0 can be further used as an educational tool to, for example, help teachers design better learning materials personalized for student profiles. Additionally, we release the code from AMoC v4.0 as open source in a Google Collab Notebook and a GitHub repository. • Introduce the Automated Model of Comprehension version 4.0 that integrates state-of-the-art Large Language models - ChatGPT. • Perform 3 in-depth psychological validation studies to support the model's adequacy in modeling reading comprehension. • AMoC v4.0 aligns with theoretical frameworks, namely Construction-Integration and Landscape models. • The model outperforms its predecessor and replicates results from human psychological experiments. • AMoC v4.0 can serve as an educational tool for designing personalized learning materials. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) is an emerging concept that impacts many disciplines, such as business, marketing, tourism, gaming, human–computer interaction, and manufacturing. Surprisingly, many scholarly and practical discussions overlook the fundamental primary factors that distinguish AR from other concepts, namely, that it involves a computing device that integrates virtual content into a consumer's perception of the real world in a specific context. The current article addresses this gap in the literature by proposing the 4C framework (based on the 4Cs: consumer, content, context, and computing device; pronounced: foresee) that highlights the importance of, and interplay among these four factors. Building on configurational theory, the framework calls for the systematic identification of additional AR-relevant factors across the 4Cs. Scholars can use this framework to systematically identify research gaps and variables of interest. Practitioners across various disciplines can employ the framework to systematically assess, communicate, and develop AR use cases. • The 4C framework highlights four unique characteristics of AR: Consumer, Content, Context, and Computing Device. • Engagement with AR derives from an alignment of the 4 Cs. • The paper advances theory by using the lens of complexity theory to explain how to engage consumers in AR experiences. • The framework offers significant implications for managers and scholars. • It allows systematic approaches to assess, communicate, and develop AR applications across various disciplines. [ABSTRACT FROM AUTHOR]

Combining knowledge from research on prosocial behavior, online communication, and (online) social support, this paper examines (1) how online communication shapes the provision of online support and (2) how the provision of online support is related to wellbeing. The focus lies on the underrepresented perspective of those acting prosocially by providing support. To answer these research questions, a qualitative (n = 22) and quantitative study (n = 470) have been conducted. The results of both studies suggest that providing online social support is positively related to people's wellbeing by satisfying basic psychological needs. This relation was partially mediated by beneficence and moderated by autonomous motivation and positive feedback. The qualitative results underline the specific conditions of online communication for providing support. It connects people with shared concerns and enables the autonomous building of anonymous support communities. Moreover, asynchronous communication with reduced cues transmitted may foster positive feedback that strengthens the self-image of those acting prosocially. • This paper focuses on the perspective of those providing support online. • A qualitative and a quantitative study are combined. • Providing online support may be positively related to people's wellbeing. • Mediators and moderators of the relation are examined. • Specific conditions of online communication for providing support are highlighted. [ABSTRACT FROM AUTHOR]

Migration (irregular and forced) represents one of the major challenges the international community faces today. Inasmuch as the phenomenon of irregular and forced migration is the marker of the state of socio-economic systems around the world, the response to and the ways of navigating the resulting multi-scalar challenges mirror not only the efficiency of the global regulatory frameworks, but also our civility. Recognizing the potential inherent in sophisticated information and communication technology (ICT), specifically the blockchain technology and smart contracts, this paper focuses on the special case of "welcome centers" that irregular migrants enter in the hope of acquiring international legal protection and thus refugee status. Since the process may be time-consuming and the living conditions undignified, this paper proposes a tool, named here "responsible wallet", aka rWallet, that bears the promise of navigating some of these challenges. rWallet derives from the recognition that in modern societies ICT should serve the purpose of improving the quality of life of all people. • (Irregular) migration is the key challenge our societies face today. • Precarity and immobility are the key issues that challenge irregular migrants. • Also the receiving communities are challenged and their vulnerability rises. • Blockchain-based tools offer a way of navigating these challenges. • The rWallet is a blockchain-based tool that does it. [ABSTRACT FROM AUTHOR]

Learning sciences are embracing the significant role technologies can play to better detect, diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with the measurement of SRL processes to advance our understanding of how multimodal data can unobtrusively capture learners' cognitive, metacognitive, affective, and motivational states over time, tasks, domains, and contexts. This paper introduces a self-regulated learning processes, multimodal data, and analysis (SMA) grid and maps joint and individual research of the authors (63 papers) over the last five years onto the grid. This shows how multimodal data streams were used to investigate SRL processes. The two-dimensional space on the SMA grid is helpful for visualizing the relations and possible combinations between the data streams and how the measurement of SRL processes. This overview serves as an analytical introduction to the current special issue "Advancing SRL Research with Artificial Intelligence (AI)" and we encourage to position new research and unexplored frontiers. We emphasize the need for intensive and strategic collaboration to accelerate progress using new interdisciplinary methods to develop accurate measurement of SRL in educational technologies. • Self-regulated learning (SRL) field started using one data stream to analyse a certain SRL process with simple statistics. • We diversified our research towards the horizontal approach analysing multiple SRL processes with one data stream using more advanced statistical techniques. • As well as to the vertical approach, investigating one SRL process using multiple data streams. • Novel is an integrated approach aligning multimodal data investigating multiple SRL processes with advanced AI techniques. [ABSTRACT FROM AUTHOR]

Burnout among esports players is a serious issue affecting competitive and professional players. The present study investigated the relationship between resilience, coping, and burnout among esports players using network analysis. Esports players (N = 453; M age = 23.0 years, SD = 4.18; in the top 40% of in-game rank) who competed in one of seven popular team-based esports completed the Connor-Davidson Resilience Scale (CD-RISC-10), Coping Functions Questionnaire (CFQ; assessing problem-focused, emotion-focused, and avoidance coping), and Athlete Burnout Scale (ABO-S; assessing a reduced sense of accomplishment, physical exhaustion, and negative feelings towards esport). Responses were assessed with Least Absolute Shrinkage and Selection Operator regularised partial correlations (EBICglasso). Findings showed a distinct network of resilience factors, coping skills, and symptoms of burnout. More specifically, resilience factors were negatively associated with symptoms of burnout and positively associated with problem-focused, emotion-focused, and avoidance coping. Problem-focused coping had a strong expected influence on the network and was positively associated with multiple resilience factors. Moreover, avoidance coping had a strong influence on the network but was positively associated with multiple symptoms of burnout. Finally, a reduced sense of accomplishment (burnout) was negatively associated with multiple resilience factors and positively associated with avoidance coping. The combined results of the present study suggest that resilience and coping are important factors for understanding burnout among esports players. • This is the first paper to use a Network Analysis to explore burnout, resilience, and coping among esports players. • Resilience factors were negatively associated with symptoms of burnout. • Resilience factors were positively associated with problem-focused coping. • Avoidance coping was positively associated with symptoms of burnout. [ABSTRACT FROM AUTHOR]

Avatars and social robots offer new opportunities for communication and raise questions about how trust is built and maintained in hybrid social interactions. We wonder what kind of trust people build with these technologies, especially where they are no longer simply tools but rather partners in interactions and affective exchanges involving vulnerability and reciprocity. Following the PRISMA guidelines, we conducted a systematic review on how trust in humans and technology can be shaped by social touch, which is the bodily contact occurring between two or more parties that express and share affective signals. Based on the n = 15 papers that meet the inclusion criteria, the evidence on the power of social touch to facilitate trust appears limited. Especially in the realm of technology-mediated interactions, mixed and inconclusive results emerge in different social contexts. Individual differences and neurophysiological correlates that could shed light on the effects between touch and trust are rarely investigated. Our positive proposal is that future studies should overcome the divisive conceptualisation of trustor and trustee, and rather explore the phenomenon of trust as a two-person bridge built in synergy between the parties. Outlining some key directions for future research, we discuss the extant solutions and applications of technology-mediated social touch, delving into the sensory and contextual factors that make it similar but different to unmediated social touch. We propose that if social touch were to be effective in promoting trust in specific technologies, this would have important consequences on various application domains such as telecommunication, healthcare, and education. • Trust in a specific technology is crucial when the technology is not only a tool but also a social partner. • Social touch has the power to make us feel connected to others and potentially help us build trust. • Evidence on the effects of mediated or unmediated social touch on trust is limited, mixed and inconclusive. • Future research on mediated interactions should delve into the sensory and contextual aspects of social touch to boost trust. • We need new ways of interacting through mediated social touch, tailored to the specificities of technology and human parties. [ABSTRACT FROM AUTHOR]

Every day we trust other individuals as we engage in social interactions in which various desirable outcomes depend on others acting the way we hope, or they have indicated. Trust extends beyond specific individuals, however, as we might trust unknown others – individuals, institutions, corporations, and governments. Some also say that we trust various artifacts, such as machines. But what is the basis of trust, and can we really trust technology? Trust is intimately connected to the notion ethos from the study of rhetoric and human persuasion, which is often used to describe various characteristics of the speaker, the audience, the relationship between the speaker and the audience, and the wider context in which communication and interaction occurs. In this article I explore to what degree machines can be considered to have ethos, and consequently whether ethos is a useful concept for understanding persuasive and credibility-related situations in HMI and by extension key aspects of human-machine trust. This allows us to draw on a long lineage of research from, for example, rhetoric, communication studies, and cognitive and social psychology to better understand the usefulness – or not – of using the notion of trust to describe our relationship with machines. • Trust in machines partly parallels trust in humans, institutions, and artifacts. • Ethos, from rhetoric, relates to credibility and trust in human-machine interaction. • This paper explores if machines can have ethos, and how this relates to trust. • Machine ethos is about perceived credibility and not the machine's ethics. • Examining ethos enriches understanding of trust and design in HMI. [ABSTRACT FROM AUTHOR]

As social robots are increasingly designed with sophisticated simulations of human skills, it becomes essential to understand boundary conditions of people's engagement of them as mindful actors. The present paper reports a comprehensive secondary analysis of six studies (total N = 967) on the relationship between mind perception (evaluation of mental capacities) and mind ascription (explicit assignment of a mind-having status) when people consider a humanoid robot in different scenarios. Results indicate there is a context-independent, moderate link between perceptions of affective mental capacity (i.e., ability to feel emotion) and explicit mind ascription. We further found hints for a weak relationship between perceptions of reality-interaction capacity (i.e., sensory and agentic abilities) and decisions to ascribe mind that may need larger samples in order to be validated. Perceptions of social-moral capacities (i.e., evaluations of people and goals) were not a significant predictor of mind ascription. Overall, these findings highlight the pivotal role played by robots' display of affective engagement with the world for the acceptance of robots as mindful "beings" in human spheres. • Mind perception in robots does not mean people assign them a mindful being status. • Dimensionality of mind perception allows for various drivers of mind ascription. • Six studies uniformly show that perceived affective capacity is the primary correlate. • Perceptions of basic but not higher-order agency may be a secondary correlate. • Long-established position of denied mindfulness in robots is called into question. [ABSTRACT FROM AUTHOR]

In recent years, university students have reported increased symptoms of stress and anxiety, which can negatively impact their mental well-being and academic performance. However, many students do not seek or receive support for these challenges. With recent technological advances in intelligent agents and their expanding capabilities, there is a potential for intelligent agents to extend and complement mental health care interventions and enhance access to care. Recognizing that there are many further steps to developing user-centred evidence-based approaches for mental health challenges, as a first step to developing effective interventions using intelligent agents, it is important to identify design elements and functionalities that are perceived as engaging and useful by students. In this paper, we present the findings of an online survey with 1054 undergraduate students to explore students' perceptions of, and preferences for, using different types of intelligent agents (e.g., virtual agents, social robots, etc.) to support their mental well-being, specifically to cope with feelings of stress and anxiety in social situations typically encountered within a university context (e.g., engaging in a group discussion, delivering presentations, expressing opinions, etc.). Students were asked to complete a questionnaire to explore their experience of stress and anxiety in the university context, as well as their perceptions of, and preferences for using different intelligent agents as assistive tools to cope with such feelings. The results provide insights into different design elements as well as social and technical capabilities to consider when designing intelligent agents to help address stress and anxiety among university students. • We surveyed 1054 undergraduate students on using intelligent agents to manage anxiety. • Public speaking was reported as the most anxiety-provoking situation at university. • Students preferred animal-like robots and conversational agents to cope with anxiety. • Intelligent agents would help manage anxiety by providing personalized coaching. • We discuss design implications for intelligent agents supporting students' anxiety. [ABSTRACT FROM AUTHOR]

With the exponential growth of new technology, it is timely that social psychologists continue to develop new and effective solutions to old but existing problems, including prejudice. One such solution is virtual reality (VR). This critical review examines VR as a promising new media tool to reduce prejudice and improve intergroup relations. Unlike traditional prejudice reduction strategies, VR provides researchers with a high degree of experimental control and flexibility. However, VR prejudice reduction research is in its infancy, and a myriad of challenges have emerged, including the: i) difficulty of cross-study comparisons and navigation of existing literature due to lack of standardized VR methodologies; ii) limitations of adapting traditional prejudice reduction strategies into VR; and iii) the lack of measurement of behaviors. This paper critically evaluates each of these limitations and, in doing so, proposes a new working framework incorporating two dimensions, the: i) VR input device, and ii) level of interactivity and mobility in the VR environment. This framework attempts to address the lack of standardization of immersion and presence in current VR research by helping guide future VR researchers to better identify the type of research they are conducting, evaluate existing research findings, and thus make cross-comparisons in VR prejudice reduction findings more meaningful. • Highlights three main limitations of current VR prejudice reduction strategies. • Conceptual framework is developed to standardize the immersion and presence in VR. • Solutions to address the limitations of VR prejudice research is proposed. • Call attention to the importance of VR as a research tool to measure prejudice. • Future directions of VR prejudice reduction research are outlined. [ABSTRACT FROM AUTHOR]

The objective of this paper is to develop and empirically validate a conceptual model that explains individuals' behavioral intention to accept AI-based recommendations as a function of attitude toward AI, trust, perceived accuracy and uncertainty level. The conceptual model was tested through a between-participants experiment using a simulated AI-enabled investment recommendation system. A total of 368 participants were randomly and evenly assigned to one of the two experimental conditions, one depicting low-uncertainty investment recommendation involving blue-chip stocks while the other depicting high-uncertainty investment recommendation involving penny stocks. Results show that attitude toward AI was positively associated with behavioral intention to accept AI-based recommendations, trust in AI, and perceived accuracy of AI. Furthermore, uncertainty level moderated how attitude, trust and perceived accuracy varied with behavioral intention to accept AI-based recommendations. When uncertainty was low, a favorable attitude toward AI seemed sufficient to promote reliance on automation. However, when uncertainty was high, a favorable attitude toward AI was a necessary but no longer sufficient condition for AI acceptance. Thus, the paper contributes to the human-AI interaction literature by not only shedding light on the underlying psychological mechanism of how users decide to accept AI-enabled advice but also adding to the scholarly understanding of AI recommendation systems in tasks that call for intuition in high involvement services. • Attitude is associated with AI recommendation acceptance, trust and perceived accuracy. • Neither trust nor perceived accuracy is associated with the AI recommendation acceptance. • In a low-risk situation, attitude is correlated with AI recommendation acceptance. • In a high-risk situation, trust and perceived accuracy are correlated with AI recommendation acceptance. [ABSTRACT FROM AUTHOR]

Online reviews are of great importance in supporting the purchasing decision making of online consumers. With the prospering of e-commerce, increasingly fraudulent reviews are appearing on e-commerce platforms to mislead consumers, and an increasing number of consumers are worrying about being deceived in online shopping. However, little research effort has been invested in studying the impact of review credibility perception caused by online review fraud on product sales. To fill this research gap, this paper conducts empirical research on the moderating effect of consumers' credibility perception of online reviews. Here, review credibility perception, or consumers' credibility perception of online reviews, refers to the credibility or trust that consumers have in the reviews they are reading. Building on dual-process theory, this paper develops two hypotheses to understand why and how review credibility perception influence consumer decision-making behaviors. The empirical studies in this paper demonstrate that consumers' credibility perception of online reviews moderate the effect of review sentiment on product sales. This work also found that consumers' credibility perception of online reviews have a heterogeneous effect on product sales. The effect shifts the relationship between review sentiment and product sales from an inverted U-shape relationship to a monotonous positive relationship with the improvement of consumers' credibility perception of online reviews. This study has great managerial implications for platforms and vendors to improve online review management. • Effect of fraudulent reviews on product sales is explored. • How review fraud influences consumers' decision making is interpreted. • Moderating effect of review credibility perception is verified. • Review credibility perception has a heterogeneous effect on product sales. [ABSTRACT FROM AUTHOR]

This paper investigates how hedonic and utilitarian content consumption and the habitual use of social media, specifically Facebook, affect phubbing behavior. The research model was tested using a cross-sectional survey (N = 220) conducted via Prolific. The participants were chosen from among those who use Facebook as their most frequent social media service on their smartphones. The results showed that utilitarian content has a more prominent effect on phubbing than hedonic content. Furthermore, for females, hedonic content positively affects phubbing when it is consumed habitually, and the effect of habitual use on phubbing differs significantly between males and females. These results suggest that technological affordances can induce phubbing behavior differently between males and females and that social media providers should consider the customization of displayed content in a way that will not induce phubbing behavior. The results also provide implications for social contexts and different relationships. Accordingly, the consumption of hedonic and utilitarian social media content should be regulated (e.g., by parents, schools), and education regarding content consumption should be provided. This study contributes to phubbing research by providing a technological perspective on its antecedents. • For females, habitual use positively affects phubbing in the context of Facebook. • For males, habitual use does not have a substantial effect on phubbing in the context of Facebook. • Utilitarian content has a positive effect on phubbing in the context of Facebook. • Both hedonic and utilitarian content has a positive effect on habitual use of Facebook. • Hedonic content has a more prominent effect on habitual use of Facebook than utilitarian content. [ABSTRACT FROM AUTHOR]