Telematics and Informatics最新文献

Both in China and across the rest of the world, livestream shopping is developing at a considerable rate. Non-transactional consumer engagement has been demonstrated to be essential to the long-term growth of livestream commerce; however, few studies have addressed this topic. Using the socio-technical approach, the present study proposes a theoretical framework to explore the antecedents of non-transactional consumer engagement in livestream commerce. To obtain comprehensive insights into these antecedents, we employed structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA) for data analysis. According to the SEM results, multiple cues, personal focus, and identification with streamers all have a positive and significant influence on emotional support and informational support, which in turn lead to greater consumer engagement. However, immediate feedback is associated with informational support, but not with emotional support. The results of fsQCA confirm the importance of the proposed antecedents and provide configurations that increase consumer engagement. The study findings not only enrich the literature regarding livestream shopping but also provide practical insights for practitioners to make consumer engagement strategies based on their own strengths. In addition, this paper demonstrates the feasibility of hybrid methods in the livestream shopping research.

COVID-19 pandemic restrictive measures curtailed environmental stimuli and social contact while encouraging media consumption. This study investigated isolation, media use, sleep and stress factors related to involuntary phenomena with and without media content. Video game players answered an online survey (N = 397; males 70.8 %; mean age = 28.04). Experiencing intrusions during lockdown (mean = 65.81 min outdoors per day) was common: earworms (92 %), Game Transfer Phenomena (GTP) (e.g., re-experiencing game content such as images, sounds, thoughts and impulses) (91 %), intrusive thoughts/imagery (ITI) (90 %), mobile phone intrusions (MPI) (e.g., vibration, ringing) (67 %) and hallucinations (49 %). All intrusions were correlated; however, different factors were related to the likelihood of experiencing them. Time playing and time using social media were correlated with intrusions with and without media content. No correlations were found with watching something or using a computer. Older age decreased the odds of GTP, ITI and hallucinations, although factors such as stress and meeting people outside the household had higher effects. Stress, rather than isolation, media use or sleep factors, appear to have been a key factor for most of the intrusions during lockdown. Particularly younger players appear to be susceptible to intrusions with and without media content.

Deepfake videos are highly realistic manipulated videos that are often difficult to distinguish from authentic videos. The technology rapidly evolves, making deepfake videos increasingly realistic. Most research on deepfake videos is focused on the algorithmic detection of deepfakes. Less is known about the human recognition of deepfake videos. The aim of the current study was to investigate the predictors of human performance at recognizing deepfake videos. Our findings show that humans perform better at recognizing deepfake videos of familiar persons compared to deepfakes of unfamiliar persons. Next, our findings show a positive relationship between time spent on social media and deepfake detection performance, as well as conspiracy thinking and deepfake detection performance. No relationships were found between age and gender and deepfake detection performance.

Crowdfunding, as enabled by donors worldwide, has played a critical role in financially supporting military forces, NGOs, humanitarian groups, and civilians in the Ukraine-Russia Crisis. This global mobilization underscores the evolving dynamics in the modern geopolitical landscape, emphasizing the transformative power of online collective action in fundraising and organizing. This study draws on signaling theory to pinpoint success indicators in crowdfunding for Ukraine projects on GoFundMe. Recognized as an effective explanatory framework, signaling theory is used as it bridges fundraising tactics with donation behavior in crowdfunding contexts. Particularly, the research examines how emotions and semantics contributed to (or hindered) fundraising success through sentiment analysis, topic modeling, and paragraph vectors. Findings revealed that trust showcased in fundraisers’ texts and videos amplified donations. Conversely, expressions of sadness deterred donations. Furthermore, the strategic deployment of an anti-Putin narrative notably enhanced fundraising results, but this strategy was way more likely to be deployed by fundraisers based in the United States. The distinct linguistic patterns of US campaigns were so pronounced that machine learning classifiers could predict the fundraiser’s origin (US vs. non-US) with 82% accuracy based solely on language. Overall, the study sheds light on the importance of emotion regulation and “cheap talk” as functional signaling strategies that facilitate value alignment. It provides new theoretical insights and methodological feasibility of examining how strategic communication affects financial outcomes in crowdfunding.

Virtual humans’ communication of emotions in social media posts are considered heuristics of human behavior. The current study extends the Cognitive-Functional Model of Emotions to virtual influencers and investigates how social media users engage with virtual human emotions. In an experiment (N = 362), non-emotional and emotional (i.e., happy, sad, and lust) social media posts are examined for their influence on Generation Z and Millennial (18–40 years old) users’ affective responses and subsequent attitudinal and behavioral outcomes within the moderation of eeriness based on the uncanny valley paradigm. Findings indicate affective responses and attitudes are serial mediators between a virtual human’s display of emotion and social media users’ behavioral intentions, and eeriness was a significant moderator. Lust has the strongest effect, followed by happiness, sadness, and no emotion. This research elevates the Cognitive-Functional Model to discrete virtual human emotions with approach tendencies. Implications for understanding the impact of virtual humans’ emotions and sexual appeal on social media users’ engagement are discussed.

The potential of Generative AI, such as ChatGPT, has sparked discussions among researchers and the public. This study empirically explores the capabilities and limitations of ChatGPT, specifically its portrayal of environmental justice issues. Using OpenAI’s ChatGPT API, we asked ChatGPT (GPT-4) to answer questions about environmental justice issues in 3,108 counties in the contiguous United States. Our findings suggest that ChatGPT provides a general overview of environmental justice issues. Consistent with research, ChatGPT appears to acknowledge the disproportionate distribution of environmental pollutants and toxic materials in low-income communities and those inhabited by people of color. However, our results also highlighted ChatGPT’s shortcomings in detailing specific local environmental justice issues, particularly in disadvantaged (e.g., rural and low-income) counties. For instance, ChatGPT could not provide information on local-specific environmental justice issues for 2,593 of 3,108 counties (83%). The results of the binary logistic regression model revealed that counties with lower population densities, higher percentages of white population, and lower incomes are less likely to receive local-specific responses from the ChatGPT. This could indicate a potential regional disparity in the volume and quality of training data, hinting at geographical biases. Our findings offer insights and implications for educators, researchers, and AI developers.

Game live streaming has become a flourishing phenomenon worldwide, yet research has primarily focused on understanding user consumption behavior from a socio-psychological perspective, neglecting the role of technological affordances. This study addresses this gap by proposing a theoretical framework that integrates affordance-based gratifications, user identification, and user engagement. Drawing upon the uses and gratifications theory, social media engagement theory, and social identity theory, we conducted a survey with 565 participants in mainland China. The findings reveal that interactivity-based gratifications significantly influence both preliminary and further levels of engagement, while modality-based gratifications primarily impact preliminary engaging behaviors. Furthermore, user identification acts as a mediating factor in the relationship between affordance-based gratifications and engagement. These results offer valuable empirical evidence for scholars and practitioners to consider technological factors and streamers’ roles while examining user engagement on game live streaming platforms. The study suggests enhancing interactivity functions and emphasizing the role of live streamers to foster user engagement. By understanding the importance of technological affordances, this research contributes to a more comprehensive understanding of engagement in the game live streaming industry.

Metaverse is a new emerging platform that enables users to interact with each other and engage in many activities inside a collective virtual shared space. The metaverse is rapidly evolving, and it is essential to understand the perception and attitude of its potential users. Therefore, this research aims to study the users of the metaverse and obtain their opinions on some of the key variables of the metaverse. These variables include the core metaverse concept, readiness, ease of use, intention to belong to metaverse, intention to adopt, and value realization. We designed an online questionnaire that aims to measure these variables. Then, a deep analysis of the collected data was conducted using various exploratory descriptive statistics on all participants. Subsequently, we performed further descriptive and correlation analysis on the participants from Saudi Arabia, which resulted in clustering participants into three groups. The result of this work can help in understanding the current and potential users of the metaverse, especially the users from Saudi Arabia. This study will consequently help in developing the metaverse space, enhancing its features, and providing users with the best experiences. Our research contributes to the theory of the metaverse by justifying a bold value-based framework for metaverse adoption. This study also introduces three clusters, Skeptical, Unaware, and Optimists, of potential users of metaverse platforms, providing a clear description of each group.

The prevalence of chatbots in human–computer communication has significantly increased. Emojis, as a form of emotional disclosure, have gained significant attention for their potential to boost chatbot service satisfaction. However, how and when emoji usage can increase satisfaction toward chatbots is not fully examined. This paper aims to fill this gap and contribute to the rapidly evolving field of human-chatbot communication research. Through three experiments, this paper investigates and explores the role of emojis in enhancing chatbot interactions. The results reveal that emojis heighten chatbot's perceived warmth but do not necessarily augment their competence. This warmth promoting effect leads to boosted service satisfaction and is more apparent when chatbots serve hedonic purposes and are pre-programmed rather than highly autonomous. However, the warmth upshot of emojis is not as potent for chatbots as it is for humans. While this study unravels the intricate pathway of how emojis augment service satisfaction, it also extends the dialogue of the Stereotype Content Model (SCM) and propels the new wave of the Computers Are Social Actors (CASA) paradigm. Thus, this research lays down pathways for further studies in understanding the role of emotionally simulated interactions in automated technologies.

Research on digital inequalities and their societal implications has garnered significant attention from scholars around the globe, emphasizing the urgency to understand their impact on individuals' everyday lives. However, studies investigating these inequalities within educational settings from teachers' perspectives remain scarce. This study addresses this gap by examining the experiences of eight elementary school teachers in Canada through a collective case study approach. Despite diverse urban and rural backgrounds, teachers unanimously recognized digital inequalities among their students. Data collection involved semi-structured interviews that explored available technologies, usage patterns, and frequency of implementation; the development of students’ digital literacies skills; and the digital inequalities that may or may not impact students. Analyses reveal inequalities including disparities in device availability and ratio, discrepancies in the types and purposes of online engagement and skill development, and inequalities of digital confidence and empowerment. The findings highlight the prevalence and exacerbation of digital inequalities among students, underscoring the influential role of students' digital capital in shaping their digital experiences and offline outcomes. Moreover, the study reveals that the inequalities faced by teachers can further intensify the digital divide among students. Consequently, concerted efforts are needed to address these inequalities to promote more equitable access to digital resources and opportunities for all students, as well as targeted professional development for educators. This research emphasizes the importance of considering teachers' perspectives in understanding and mitigating the impact of digital inequalities on culture and society.