Telematics and Informatics最新文献

This paper analyzes a new topic in gambling among adolescents: the association between the amount of available income that is spent weekly and online gambling, and further examines the possible role of conflictual relationships as a moderator of this association. To that end, interval regression analyses are used with a nationally representative sample of Spanish adolescents (n = 38,010; M_age = 15.69; 51.4 % females). The results indicate that spent income, bullying victimization and poor-quality or conflictual relationships with the mother are positively associated with online gambling. Moreover, the last two predictors moderate the association between spent income and online gambling. The results also indicate that parents and schools have some room to maneuver. Thus, informative campaigns at school integrating parents could reduce online gambling directly and indirectly via the improvement of adolescents’ conflictual relationships. Moreover, special attention should be paid to boys, among whom most online gambling takes place.

In order to achieve interpersonal goals, people manipulate their self-image: they manifest their most favourable traits and avoid exhibiting the most aversive ones. Disgust is one of the most powerful turn-offs in a mating context. Here, we explored which disgust domain −pathogen, sexual, or moral − is considered the most damaging for self-image. We also revisited the importance of various positive traits in a potential partner. The participants (N = 1,017) played a date-simulation game. They chose which one of five positive characteristics, and which one of three disgust norm transgressions they want to manifest. We analysed the influence of one’s biological sex, sexual orientation, and culture on self-presentation during a date.

Women more often manifested morally disgusting behaviours and artistic abilities than men, while men more often manifested pathogenically disgusting behaviours and kindness. Homosexual orientation predicted lower frequency of admitting to moral disgust transgressions, and higher frequency of exhibiting artistic abilities.

As AI systems become increasingly prevalent in various aspects of daily life, gaining a comprehensive understanding of public perception towards these AI systems has become increasingly essential for several reasons such as ethical considerations, user experience, fear, disinformation, regulation, collaboration, and co-creation. In this study, we investigate how mass social media users perceive the recent rise of AI frameworks such as ChatGPT. We collect a total of 33,912 comments in 388 unique subreddits spanning from November 30, 2022 to June 8, 2023 using a list of AI-related keywords. We employ a combination of thematic and sentiment analysis, using advanced natural language processing techniques. Specifically, we use BERTopic to uncover the major themes regarding AI on Reddit. Our findings indicate that technology-focused subreddits primarily discuss the technical dimensions of AI, while non-technical subreddits more often address societal impacts, such as job displacement concerns. The disparity in focus between subreddits suggests a gap in the public understanding of AI. We leverage GPT-3.5 with zero-shot prompting and LIWC to analyze the sentiment and perception of AI among individual users. Through a comprehensive sentiment and emotion analysis, we discover that tech-centric communities exhibit greater polarization compared to non-tech communities when discussing AI topics. This suggests that individuals with a deeper understanding or familiarity with AI technologies might have more divided opinions, possibly reflecting a mix of optimism about technological advancements and skepticism about potential impacts. This research contributes to our broader understanding of public opinion surrounding artificial intelligence.

Narcissism, as a form of self-awareness of self-importance or self-influence, can be characterized by a constant attention to success and the need for authority, competitiveness, and grandiose, which may be introduced to promote the attractiveness of a project. This study analyzes the effect of textual narcissism on the willingness to back citizen science projects by considering the social roles of the citizen project owners: expert, student, and amateur researchers. This paper uses social role theory to anchor the seven forms of narcissism and proposes 9 dimensions of narcissism, which are then classified into 3 categories: social role advantage, psychological superiority, and identity aspiration. Using a web crawler, 850 citizen science projects are employed as a corpus. Text mining is used to quantify the narratives, and econometric models are applied to estimate the effect of textual narcissism. This study reports that narcissism presents an inverted U-shaped effect. On social role, formal researchers (experts and students) receive lesser degrees of public tolerance to textual narcissism, over amateur researchers. By extending narcissistic influence and social role theory to citizen science, this paper can guide stakeholders and regulators such as scientific experiment platforms in generating suitable text descriptions for better research resource mobilization.

In this paper, we examine new and emerging uses of artificial intelligence (AI) and automated decision making (ADM) across various aspects of work, namely hiring, job redesign, and team formation, and their impact on disabled people. Building on disability as both a generative form of embodiment and knowledge, we consider how AI and ADMs can enable and empower disabled people for work, but also their inherent problems and contradictions. We ask the following questions: What are the implications for disabled workers? And importantly, how can we make these systems fairer and more inclusive, especially for disability?

This paper examines public attitudes regarding the privacy of personal communications across several African countries. The study additionally investigates factors influencing an individual’s expression of the right to privacy and rejection of state surveillance. Descriptive and logistic regression analyses were conducted on survey data gathered from 48,084 interviews completed in 34 countries. The findings reveal that, among the surveyed countries (34 out of 54 on the continent), a majority (54.87%) advocate for the protection of private communications. This indicates an increasing inclination among individuals to assert greater control over their personal information, which is being collected and utilized by governmental organizations and often by extension, private entities. The results demonstrate that education, gender, occupation, institutional trust, frequency of newspaper reading, perceptions of social media, attitudes towards internet regulation, opinions on government accountability, and the frequency of internet usage all significantly influence an individual’s stance on personal data privacy. Governments must strive for more effective communication with citizens to foster support for surveillance programs that achieve a delicate equilibrium between state security and the protection of privacy rights. This study provides an evidence base that policymakers, practitioners and academics can utilize to make informed decisions about data privacy attitudes and predict privacy actions.

The anthropomorphic features of humanoid social robots (HSRs) have been contended to hold significance in understanding users’ behavior regarding HSRs. However, there is a lack of research examining how HSRs’ different anthropomorphic features could trigger users’ cognitive and behavioral responses. Utilizing social response theory as a foundation, our study presented a research model for scrutinizing how three different anthropomorphic features—appearance, voice, and response, influence users’ cognitive (perceived social presence and perceived humanness) and behavioral responses (continued usage intention) to HSRs. Data gathered from hotel customers (N = 509) from a survey posted online was utilized to validate the research model. Results showed that appearance and response positively affect perceived social presence, whereas appearance, voice, and response positively affect perceived humanness. Further, both perceived social presence and perceived humanness were found to positively influence continued usage intention. This research enriches the current literature on social robots by explaining how various anthropomorphic features as social cues could trigger user cognitive and behavioral responses differently from the social response lens.

The world’s largest transnational fandom community of the BTS (BangTan Sonyeondan) ARMY (Adorable Representative M.C. for Youth) is structured to achieve common goals and exert influence. To identify a mechanism that explains the organizational structure of transnational virtual communities, we empirically investigate how the global fandoms carry out autonomous activities and adapt to the environment without coercive governance despite their massive size and complexity. Using the techniques of social network analysis and viable system model, we found some structural differences between the online communities with a viable and non-viable structure. First, the BTS ARMY network is sustained by a systematic structure of key players who voluntarily play distinct roles. In contrast, the Arianator network is relatively unorganized and dispersed. Moreover, multi-fandom accounts can act as potential user acquisition roles. Finally, two different diffusion types, text-based information and image-based media, are carried by distinct roles of subsystems. As one of the first studies to empirically examine the viability of online transnational fandom from an organizational structure perspective, this paper provides practical implications for fandoms from three perspectives; (1) resource mobilization and sustainability, (2) influence of fandom dynamics, and (3) economic impact. The results suggest that fandoms taking strategic actions upon the viable structure on digital platforms could represent a new cultural hegemony, promoting global unity and pop cosmopolitanism.

This study explored the potential of eXplainable Artificial Intelligence (XAI) in raising user awareness of algorithmic bias. This study examined the popular “explanation by example” XAI approach, where users receive explanatory examples resembling their input. As this XAI approach allows users to gauge the congruence between these examples and their circumstances, perceived incongruence then evokes perceptions of unfairness and exclusion, prompting users not to put blind trust in the system and raising awareness of algorithmic bias stemming from non-inclusive datasets. The results further highlight the moderating role of users’ prior experience with discrimination.

Despite the recognized potential of artificial intelligence (AI) to improve governance, a significant divide in AI adoption exists among governments globally. However, little is known about the underlying causes behind the divide, hindering effective strategies to bridge it. Drawing on the AI capability concept and the Technology-Organization-Environment (TOE) framework, this study employs Explainable Artificial Intelligence (XAI) models to analyze the multifaceted factors influencing AI adoption by governments worldwide. The results underscore the critical roles of internet security and internet usage within the technological dimension, regulatory quality, government effectiveness, government expenditure, rule of law, and corruption control within the organizational dimension, and globalization, median age and GDP per capita within the environmental dimension. Notably, our analysis explores the intricate effects of these variables on government AI adoption, identifying inflection points where their impacts undergo significant shifts in magnitude and direction. This nuanced exploration provides a comprehensive understanding of government AI adoption globally and illustrates targeted strategies for governments to bridge the AI adoption divide, making theoretical, methodological and practical implications.