Telematics and Informatics最新文献

Governments and social media platforms strive to combat the spread of online rumors by fostering a positive public atmosphere of rumor combating. However, the effectiveness of this approach remains uncertain, as do the underlying mechanisms through which public atmosphere mobilizes social media users against rumors. Leveraging insights from psychological attachment theory and ethics research, this study aims to examine the mediating mechanisms and boundary conditions for the relationship between public atmosphere and rumor-combating participation (RCP). This empirical study employed a hypothetical scenario method to design two scenarios (i.e., strong vs. weak public atmosphere of rumor combating), and collected 331 valid responses using the MTurk platform. The results provide empirical evidence that public atmosphere significantly facilitates RCP. Moreover, high-level psychological attachment (i.e., identification and internalization) fully mediates the relationship between public atmosphere and RCP, but low-level psychological attachment (i.e., compliance) does not act as a mediator. Further examination of the boundary conditions revealed that moral judgment positively moderates the relationship between public atmosphere and psychological attachment (both high-level and low-level). However, anticipated guilt only exerts a positive moderating influence on the relationship between public atmosphere and low-level psychological attachment. This study provides fresh insights by revealing that public atmosphere can promote RCP by enhancing high-level psychological attachment, while uncovering the distinct moderating roles played by moral cognition and emotion in the process. Therefore, this paper not only advances our theoretical understanding of why and under what conditions public atmosphere influences RCP, but also offers practical insights into strategies for mobilizing social media users to combat rumors.

Artificial intelligence is believed to facilitate cost-effective and clean energy by optimizing consumption, reducing emissions, and enhancing grid reliability. Approaches such as non-intrusive load monitoring (NILM) offer energy efficiency insights but raise ethical concerns. In this paper, we identify most prominent ethical and societal issues by surveying relevant literature on smart metering and NILM. We combine these findings with empirical insights gained from qualitative workshops conducted with an electricity supplier piloting the use of AI for power load disaggregation. Utilizing the requirements for trustworthy AI, we show that while issues related to privacy and security are the most widely discussed, there are many other equally important ethical and societal issues that need to be addressed, such as algorithmic bias, uneven access to infrastructure, or loss of human control and autonomy. In total, we identify 19 such overarching themes and explore how they align with practitioners' perspectives and how they embody the seven core requirements for trustworthy AI systems defined by the Ethics Guidelines for Trustworthy AI.

While extensive research has explored user engagement with misinformation, there remains a gap in understanding how individuals respond to those who share misinformation by blocking them. This study explores the factors influencing this blocking behavior, including social media news consumption, psychological traits, personality, and cognitive characteristics. Through three studies conducted in varying political contexts (the US and Singapore) and focusing on different types of misinformation (political, health, and political and entertainment deepfakes), we employ the dual motivation framework to analyze the interplay between social media news consumption and the decision to block sources of misinformation. Additionally, we investigate the role of the fear of missing out as a mediator in this relationship and how traits such as conscientiousness and cognitive ability moderate it. Our findings suggest that individuals who frequently consume social media news are more inclined to block sources of misinformation due to a heightened fear of missing out. Furthermore, those with lower levels of cognitive ability and conscientiousness exhibit a greater tendency to block misinformation sources. This research enhances our understanding of the mechanisms driving blocking behavior on social media in response to misinformation and underscores the importance of considering sociopolitical factors in understanding such behaviors.

Whether in social media, in news services, or via instant messaging systems - in places where people communicate online, one can occasionally encounter internet trolls. Trolls are real people, who engage in destructive, aggressive, or disruptive behavior online, usually under the protection of anonymity. In this cross-sectional study the relationship between grandiose and vulnerable narcissism, self-esteem, aggression, and trolling behavior was investigated on the basis of four assumptions. To test the hypotheses, data from 149 participants were analyzed. The results indicated that aggression and trolling behavior were positively related. Significant positive correlations of both forms of narcissism with aggression and trolling behavior were obtained. Finally, the extent to which self-esteem exhibits a moderating influence on the association between narcissism and trolling was examined. Specifically, high self-esteem was shown to weaken the correlation between narcissism and trolling behavior. Therefore, high self-esteem neutralized the unfavorable impact of high narcissism on trolling. The findings may serve to better understand the personality structure of trolls and the psychological mechanisms involved in their internet trolling behavior.

Although virtual reality (VR) has been shown to be an effective means of delivering news stories, there is still a lack of understanding as to how VR can complement specific narrative formats, such as textual news, in journalism. This study investigates the impact of using VR (vs. 360° video on a 2D screen) to deliver textual news with high (vs. low) narrativity in terms of triggering issue involvement through three immersion-related psychological responses (empathy, transportation, and identification) within the realm of disaster journalism, wherein victims’ experiences are conveyed to users. The results of a between-subject experiment (N = 144) showed that VR (vs. 2D) reported higher transportation. Moreover, VR (vs. 2D) elicited greater empathy when used in conjunction with the textual disaster news with high (vs. low) narrativity, which further increased issue involvement. These findings provide insights that are expected to be helpful in harnessing the potential of VR for narrative storytelling in journalism, which can provoke an empathetic and visceral understanding of victims in disaster news.

During the COVID-19-related lockdowns around the world, individuals received a permanent digital stream of information about the pandemic via their smartphones. We theorize that such excessive COVID-19-related smartphone use can affect information overload, i.e., the perception of being exposed to too much information about COVID-19. We also introduce the notion of infection self-efficacy, the feeling that one is able to control the likelihood of being infected. We conducted a two-wave panel survey among an adult sample in Austria (N_T2 = 416) during the first lockdown in 2020. Findings of a metric measurement invariant structural equation model revealed that excessive smartphone use predicts information overload over time. Moreover, information overload resulted in lower infection self-efficacy after one month. Reciprocal effects showed that information overload at T1 also increased excessive smartphone use at T2, suggesting a spiral. However, infection self-efficacy did not predict information overload and excessive smartphone use over time. Our findings contribute to the literature on information processing mechanisms by providing clear evidence for the reciprocal relationship between excessive smartphone use and information overload over time. The findings are also important for health scholarship because they explain individuals’ perceptions about whether they are able to protect themselves from COVID-19.

User interaction within social media groups is increasingly vital for offering social support to individuals experiencing mental health issues. However, measuring social support in these online communities is challenging due to the dynamic and complex nature of user interaction, which conventional research methods struggle to capture. To cope with the challenge, we propose a mixed-measurement approach that combines network theory and social support perspectives to enhance existing measures. Our methods offer a more comprehensive understanding of social support online by estimating emotional spread within these communities and examining the impact of information exposure and government control on community activities and users’ mood stability. Our findings highlight the importance of considering multiple dimensions and factors when measuring social support in social media groups, adding insights into the underlying mechanism of social support cultivation on social media platforms.

While both theory and empirical evidence have established the critical role of digital infrastructure in promoting innovation, there needs to be more understanding of factors mediating this nexus, especially from the African context, which is understudied. This paper argues that digital infrastructure spurs innovation, but the overall effect depends on countries’ level of human capital. Relying on data from 28 African countries spanning 2011–2019 and the system Generalized Method of Moment (GMM) estimator, this study departs from the extant literature by examining the synergistic effect of digital infrastructure and human capital on innovation while placing much emphasis on the multidimensional measurement approach of digital infrastructure. The results show a positive relationship between digital infrastructure and innovation in Africa. Furthermore, the interactive effect of digital infrastructure and human capital is significantly related to innovation, implying that digital infrastructure can indirectly enhance innovation through human capital accumulation. To promote innovation, the study recommends that policies that improve digital infrastructure should be pursued simultaneously with policies that enhance human capital.

In recent years, continued advancements in 5G and other communications technologies, coupled with the disruptions in physical interactions brought about by the COVID-19 pandemic, have drawn global attention and capital to the metaverse. In this context, the present study was conducted with the aim of developing and validating multidimensional usage motivation factors that capture the unique properties of the metaverse. In addition to extensive literature research, a Delphi study was conducted with a group of 30 professionals to derive the initial items for metaverse usage motivation. Those items were then used to devise a questionnaire that was in turn administered to 1000 metaverse users. Exploratory and confirmatory factor analysis resulted in 13 items based on four factors: communication, experience of new worlds, self-expression, and economic activity. Both convergent and discriminant validity were verified between the factors. Finally, correlation analysis was used to verify the nomological validity of the scale. Metaverse usage motivation, when identified as described in this study, is expected to serve as a useful tool that can be measured more objectively than the existing concept of metaverse usage motivation, as the measurement tool described herein reflects the opinions of actual metaverse users and experts. It is also expected to be used in various contexts as a measurement variable in subsequent studies examining metaverse user usage behavior.

The primary aim of this study is to examine citizens' intentions to adopt meta-government (or metaverse government) by investigating the influence of various enablers and barriers on adoption intentions. Drawing upon the Technology Acceptance Model, this research utilizes a dual factor approach to examine how herd behavior, perceived ease of use, perceived usefulness, perceived cyber risks, and resistance to change impact intentions to adopt meta-government. A total of 371 responses were collected and analyzed using Structural Equation Modeling. The results highlight the significance of herd behavior, perceived ease of use, and perceived usefulness in facilitating adoption intentions, while perceived cyber risks negatively affect both adoption intentions and perceived usefulness. This study contributes original insights into the key facilitators and obstacles citizens encounter when considering meta-government adoption, addressing a gap in the literature.