Background: The emergence of virtual social networks has facilitated a new form of marital infidelity known as internet infidelity.Aims: This study investigated the mediating role of self-esteem in the relationship between self-compassion, relationship maintenance behaviors, and attitudes toward internet infidelity.Methodology: A cross-sectional study using SEM was conducted among 481 Iranian married users. The data collection was performed using Internet Infidelity, Relationship Maintenance Strategies, Self-Compassion, and Self-Esteem Questionnaires. SEM was used to examine hypothesized relationships, and the bootstrap in Preacher and Hayes’ Macro program was employed for testing mediation.Findings: SEM analysis revealed that self-compassion and relationship maintenance behaviors had a direct effect on both self-esteem and attitudes toward internet infidelity (P< 0.0001). However, the hypothesized mediating role of self-esteem was not supported. These findings underscore the significant influence of self-compassion and relationship maintenance behaviors in predicting attitudes toward internet infidelity.Conclusion: Counseling interventions aimed at fostering self-compassion and reinforcing relationship maintenance skills may help reduce the risk of internet infidelity.
Background: With the advent of online social networks, some new form of life was developed in a virtual environment and the relationship among people became different from its traditional form.Aims: The present study examines the status quo of the use of one of the most popular social networks in Iran, namely Instagram, and the typology of its users.Methodology: The data was collected using a questionnaire and almost 1000 Instagram users answered the questions. In order to understand the use of Instagram and the typology of its users, the theoretical concepts of "uses and gratifications", "transition from audience orientation to user orientation", "online identity", "networked individualism" and "cyberloafing" were examined.Findings: The daily use of social networks by users is an average of 139 min, of which approximately 104 min are dedicated to Instagram, and that there was a significant relationship between the use of Instagram and the age group, marital status, and social classes.Conclusion: Instagram users comprise a spectrum from passive consumer actors to active producer actors. Different user types based on the use motives are: instrumental/commercial users (consumer or passive and productive or active), interactive users (social communicator and relationship builder), information seeking users (wide scope information seeking and local scope information seeking), disclosing users (aesthetic and lifestyle), loafing users (tourists and celebrities) and specialty-oriented users.
Background: Background: Four of the top ten subscribed YouTube channels feature child-centric content, with three belonging to kidfluencers whose videos are dubbed in fourteen languages. By mid-2025, these four channels collectively garnered 608 million subscribers, demonstrating the phenomenon's significance in the digital sphere.Aims: This article utilizes the Dual-Spacization of the World paradigm and a qualitative approach (combining participatory observation and documentary analysis focused on YouTube and the popular unboxing genre) to describe the kidfluencer phenomenon, its links to digital commerce and economy, and its cultural consequences on child development and socialization.Methodology: The second part offers a local interpretation of this global trend by analyzing thirteen semi-structured interviews with children and adolescents (aged six to fourteen).Findings: The analysis confirmed the interviewees' positive alignment with kidfluencing through four key themes: "Spectacular Consumption and the Spectacularization of Consumption", "Perceiving Kidfluencers as Independent and Validating Them", "Expert Users, Potential Producers" and "Kidfluencing: A Path to Fame, a Shortcut to Wealth".Conclusion: The study’s findings recommend that, to maximize opportunities, supportive legislation and regulatory bodies should actively back children’s agency and capabilities in digital environments, while simultaneously promoting the development of spatial literacy and enhancement of children’s digital literacy through national and global programs and policies.
Background: Artificial intelligence (AI) is transforming global economic systems, reshaping labor markets, industries, and geopolitical power structures. The Age of AI and Our Human Future by Kissinger, Schmidt, and Huttenlocher (2021) offers an influential perspective on these transformations, warranting systematic academic analysis.Aims: This study aims to examine the major economic and societal themes emerging from The Age of AI and Our Human Future and to interpret their implications for the future of the world economy in the age of AI.Methodology: Using Braun and Clarke’s (2006) six-phase thematic analysis, the book was analyzed as the primary qualitative data source. The theoretical framework combined the concept of Disruptive Technologies and Schumacher’s human-centered perspective to interpret how AI influences global economic and ethical structures.Findings: Four key themes were identified: (1) Transformation of Industries, (2) Labor Market Shifts and Economic Inequality, (3) AI and Global Power Dynamics, and (4) Regulation and Ethical Frameworks. The findings show that AI drives innovation and productivity while intensifying inequality and geopolitical competition. Ethical and regulatory frameworks are essential to balance technological progress with social justice and human welfare.Conclusion: AI’s rapid development is reshaping the world economy, necessitating interdisciplinary approaches and global cooperation. Human-centered and ethically governed AI development is vital to ensure that technological progress contributes to equitable and sustainable global prosperity.
Background: This article presents the findings of our specially designed study based on data from the GSS 2022 comprehensive survey. We wanted to investigate the landscape of psychological support in the contemporary American workplace. As the significance of employee well-being grows, organizations recognize the need to provide effective psychological support to foster a healthy work environment.Aims: Our study aimed to evaluate psychological support programs' awareness, availability, utilization, and perceived efficacy in various industries and organizations, particularly in relation to Internet use.Methodology: A varied group of American citizens took part in the study, answering questions related to their awareness of available resources, involvement in workplace support initiatives, and the effects on their overall well-being.Findings: The findings suggest that employees’ perception of psychological support from managers positively influences both work and life satisfaction. However, only a portion of the original hypotheses concerning the relationships between this perception and other variables were supported by the data.Conclusion: Notably, it was discovered that younger individuals tend to perceive less psychological support from management. Additionally, individuals previously married, regardless of their current marital status, were more likely to perceive their managers as psychologically supportive. In addition, those with a higher level of education reported a higher level of perceived employer support. And, balanced daily internet engagement can enhance the perception of support.
Background: Nigeria's rapid digital transformation has led to increased cyber risks, endangering the country's security and stability. Although various policies and guidelines have been developed on cybersecurity, it is not yet clear how effective they are when compared to global benchmarks.Aims: This literature survey compares cybersecurity governance in Nigeria with developed countries, identifies shortcomings and offers recommendations for improvement.Methodology: Through qualitative data analysis, the study highlights weaknesses in laws and regulations, lack of cybersecurity awareness and training, corruption issues, infrastructure, housing shortages and poor economic integration. Comparing global practices with countries such as the UK, the US and Estonia, the study reveals that Nigeria lags behind in key areas such as law enforcement and the concept of work.Finding: The recommendations include reforming the regulatory framework to respond to emerging threats, promoting stronger public-private partnerships, expanding awareness and training, and adopting Recognize global best practices in cybersecurity governance.Conclusion: Improving these aspects will help Nigeria strengthen its ability to defend itself against evolving cyber threats and better align with global standards.
Background: The evolution of monetization models and marketing approaches in the digital industry has redefined the growth trajectories of startups.Aims: This study explores monetization strategies in India’s gaming startup ecosystem, examining their influence on user behavior, preference, revenue retention and venture capital (VC) attraction.Methodology: Aligned with a focus on the microstructure of the gaming market, investor behavior, and capital markets, the research employs a mixed-method framework combining interviews, surveys, and MICMAC analysis, grounded in Rational Choice (RC) theory. Using Mobile Premier League (MPL) as a case study, the present research evaluates three monetization models: Real Money Game (RMG), Free-to-Play (F2P), and hybrid strategies.Findings: Key findings indicate that RMG significantly enhances user engagement while demonstrating a stronger signaling effect for VC attraction. Empirical results suggest that the RMG monetization strategy offers greater potential for investors decision-making and ensures more robust revenue continuity compared to F2P and hybrid alternatives.Conclusion: The study contributes to the literature by bridging behavioral finance and capital market governance within the context of digital innovation in emerging economies.
Background: Advertising, which has been defined as, a systematic effort to shape people's opinions, attitudes and behaviours in a specific direction is a significant part of public communication. Nowadays, video advertisements are among the most important tools to attract different tastes.Aims: It is crucial to examine whether commercial advertisements shape gender stereotypes in a given society.Methodology: This study seeks to examine gender stereotypes in the Indian most watched video advertisements on YouTube from 2015 to 2021 using Barth’s semiotic and Goffman’s dramaturgy approaches.Findings: There is consistency between the gender of the actor and the voice of the narrator, the way of touching objects, the ritualization of subordination and the type of presence in the family and society as well as licensed withdrawal in Indian video advertisements that have the highest views on YouTube.Conclusion: The overall result indicates the presence of solid gender stereotypes in advertisements.
The rapid diffusion of generative artificial intelligence as a primary interface for information-seeking has introduced a new and underexplored dimension of power in contemporary societies. As hundreds of millions of users worldwide increasingly turn to large language models for answers to everyday questions, the corporations that develop and deploy these systems have gained an unprecedented capacity to shape what people know, how they reason, and whose version of the world prevails. Drawing on Shoshana Zuboff's theory of surveillance capitalism and Michel Foucault's analytics of power/knowledge, this article argues that the competition among major technology firms in the generative AI sector is not merely commercial but fundamentally epistemic. Through a review of recent empirical data on AI adoption and a critical analysis of market concentration, the article demonstrates that a small number of corporate actors— operating with limited public accountability and considerable opacity— are consolidating control over the epistemic infrastructure of daily life. This concentration reproduces and deepens existing asymmetries of knowledge, raising urgent questions for democratic governance. The article concludes by calling for the reconceptualisation of AI information systems as public epistemic infrastructure, subject to transparency requirements, independent auditing, and democratic oversight.
Background: The principle of dual criminality, which requires an act to be criminalized in both the requesting and requested states, is a cornerstone of mutual legal assistance. However, the rise of cybercrime, characterized by its borderless nature and reliance on perishable electronic evidence, has created significant challenges. Divergent legal definitions, procedural variations, and evidentiary standards frequently delay or obstruct cross-border investigations.Aims: This paper examines the limitations of dual criminality in cybercrime investigations and explores how technological advancements and inconsistent domestic frameworks affect international cooperation.Methodology: A comparative legal analysis is employed, drawing on the legal systems and practices of Rwanda, Germany, Estonia, and Hungary. These jurisdictions were selected to represent non-EU and EU states with diverse legal traditions. The study also evaluates key international instruments, including the Budapest Convention and its Additional Protocols, alongside mechanisms such as the European Investigation Order.Discussion: Findings reveal structural and procedural barriers, such as inconsistent offence definitions, jurisdictional conflicts, and inadequate technical capacity, which hinder timely and lawful evidence sharing. These gaps undermine trust and efficiency in cooperation.Conclusion: The paper recommends harmonizing cybercrime definitions, adopting technology-adapted dual criminality assessments, implementing fast-track evidence-sharing mechanisms, and strengthening mutual trust through capacity-building and rights-protection measures. These steps aim to reconcile dual criminality with the urgent need for efficient and rights-compliant international collaboration.
Background: Contemporary debates on disinformation are dominated by two influential approaches: Fallis’s functional (teleological) model and Simion’s purely epistemic Disinformation as Ignorance-Generating Content (DIGC) model. Their respective strengths and weaknesses become salient in real-world settings such as the Backfire Effect, the spread of bullshit, and disputes about the epistemic status of Large Language Models (LLMs).Aims: We aim to (i) critically evaluate the explanatory and classificatory utility of the functional and purely epistemic models across these scenarios, (ii) diagnose key failure modes (especially DIGC’s over-generation and the functional model’s difficulties with non-intentional sources), and (iii) propose a more extensionally adequate framework.Methodology: We conduct a comparative conceptual analysis of both models and test their classifications against several cases. In particular, we use empirical findings on the Backfire Effect to examine whether a purely consequence-based criterion misclassifies accurate, well-intentioned scientific information. We also incorporate Frankfurt’s distinction between lying and bullshit to refine how epistemic malice is characterised.Findings: Fallis’s functional model captures complex forms of disinformation (including true and adaptive disinformation) by tying disinformation to a misleading function, but it struggles to classify outputs from non-intentional sources such as autonomous AI. DIGC broadens coverage by removing intentionality and focusing on dispositions to increase ignorance, yet this purely epistemic stance yields an Over-generation Problem: under Backfire conditions, it can wrongly classify accurate and well-intentioned scientific communication as disinformation. To address these limitations, we propose a hybrid teleological framework, Functional-Contextual Disinformation (FC-DIGC), which combines DIGC’s consequence criterion with a teleological constraint requiring a misleading function. This synthesis better separates malicious deception (disinformation) from unintended epistemic harm (contextually harmful misinformation) and helps clarify how LLM outputs should be categorised.Conclusion: A hybrid teleological approach improves extensional adequacy by preventing over-generation while retaining coverage for non-intentional systems. FC-DIGC provides a principled way to distinguish disinformation from contextually harmful misinformation and, by integrating the lying–bullshit contrast, captures a broader spectrum of epistemically motivated malice relevant to contemporary information environments, including AI-mediated communication.
Background: Cyberspace has evolved into a vast and intricate cultural ecosystem in which the boundaries between communication, cognition, and creation are constantly being redefined.Aims: This study examines how digital interactivity restructures the semiotic logic of narrative meaning-making within contemporary cyberspace, using Detroit: Become Human as a paradigmatic case of interactive digital narrative. The research aims to determine how multimodal signs, procedural architectures, and player agency interact to produce dynamic and networked processes of semiosis.Methodology: Through an integrative semiotic framework, encompassing multimodality, interactive agency, and branching narrative design, the analysis demonstrates that meaning in the game emerges not from fixed textual structures but from recursive exchanges between human interpretation and algorithmic responsiveness.Findings: The findings reveal that the game’s interactive architecture generates a self-modifying semiotic environment in which choices function as sign-acts that reorganize symbolic patterns across divergent narrative trajectories. This networked mode of signification reflects the broader cultural logic of cyberspace, where meaning is co-created through participatory, decentralized interaction rather than linear authorial transmission.Conclusion: The study concludes that interactive digital narratives constitute a distinctive semiotic paradigm, one that transforms storytelling into a collaborative and cybernetic process of meaning construction. These insights offer a foundation for future research on how digital media, algorithmic systems, and user participation jointly reshape contemporary forms of narrative and cultural signification.
Background: In the age of algorithmic media, TikTok has become a significant informal learning space for Generation Z, especially in shaping perceptions of ethics, power, and justice.Aims: This study examines how final-year Library and Information Science students at the University of Ilorin engage with TikTok’s “silent curriculum”, a set of implicit and emotionally charged lessons embedded in short video content. Guided by informal learning theory, critical media literacy, and research on algorithmic governance, the study investigates how students interpret and absorb ethical and civic messages encountered on the platform.Methodology: Using qualitative design, 12 active TikTok users reflected on the platform’s educational influence. Data collection was through semi-structured interviews and digital diaries over four weeks.Findings: The students often encounter content related to social justice, mental health, gender identity, and political commentary, commonly communicated through humour, storytelling, and aesthetic trends. These engagements support reflection and awareness, yet they are shaped by algorithmic patterns that promote particular narratives while limiting others. The study shows that TikTok can serve both as a participatory space for civic learning and as a platform where performative ethics and misinformation circulate. For Library and Information Science students, this raises important questions about their future responsibilities as ethical managers of digital content.Conclusion: The paper recommends a redesign of digital literacy approaches to include emotional awareness, ethical judgement, and understanding of platform structures. By centring the perspectives of Nigerian Gen Z students, the study adds to knowledge on how digital platforms act as instructional agents in contemporary civic learning.
ackground: Over the past decade, advances in machine learning, natural language processing, and generative artificial intelligence have enabled news organizations to automate routine reporting tasks, enhance investigative capabilities, and deliver content tailored to increasingly segmented audiences.Aims: This paper presents a systematic review of scholarly literature on the integration of AI into journalism, covering studies published between 2010 and 2025.Methodology: Drawing on research from diverse geographical contexts and methodological approaches, it synthesizes findings on AI’s technological capabilities, its economic and ethical implications, and its broader societal impact on the news ecosystem.Findings: The review identifies AI’s transformative role in automating routine reporting, enhancing investigative journalism, enabling personalized content delivery, and streamlining newsroom operations. However, it also reveals significant concerns regarding transparency, accountability, bias, audience trust, and the erosion of human editorial oversight. The findings highlight regional disparities in adoption, shaped by technological infrastructure, market readiness, and policy environments, underscoring the need for context-sensitive approaches to AI governance. By mapping prevailing trends and identifying underexplored dimensions—such as cross-cultural differences in adoption, long-term effects on democratic deliberation, and evolving newsroom ethics—this study provides an evidence-based foundation for policymakers, media professionals, and researchers.Conclusion: While AI holds the potential to enhance journalism’s efficiency, reach, and innovation, its responsible implementation requires robust ethical standards, governance frameworks, and sustained human involvement to safeguard the profession’s democratic role.
Background: The economy wrongly commodifies attention. The commodification is morally objectionable because our attention is not properly subject to market forces.Aims: A crucial aim of this article is to broaden the debate about the attention economy.Methodology: Conceptual analysis of the attention economy, the right to attention, and the influence of market forces on commodities.Discussion: In the first section, I survey the conventional approach to the attention economy, which treats the ethical problems here as instances of questions about the moral limits of markets. I agree that this approach is justified, but I aim to broaden the debate by focusing on whether attention should be commodified at all. In the second section, I argue that attention is not properly subject to market forces. In the third section, I argue that subjecting attention to market forces leads, predictably, to the development and use of technology that violates the right to attention. In the fourth section, I argue that coercive paternalism offers the correct response to these problems and that two other solutions— the reliance on nudges and the reliance on social antibodies— are inferior.Conclusion: The attention economy is a rights-violating and noxious market. Its wrongful commodification of attention produces a market that does not respect the boundaries between commercialized and non-commercialized spaces.
Background: Beyond being a mere technical tool, Artificial Intelligence (AI) is a socio-political phenomenon that redefines the identity, social, and political structures of developing nations.Aims: This study analyzes the mechanisms of "algorithmic dependency" and its consequences on national identity, social cohesion, and political development, with a specific focus on Iran.Methodology: Employing a qualitative approach and an analytical case study strategy, this research utilizes systematic documentary research. Findings are interpreted through the theoretical lenses of the "Social Construction of Technology" (SCOT) and the "Digital Divide", ensuring validity via data triangulation.Findings: The results indicate that the algorithmic monopoly of global powers fosters "digital colonialism" and erodes political agency. In Iran, the intersection of cultural biases in imported algorithms with a "structural lag" in governance facilitates "silent othering" and social polarization. Furthermore, by engineering citizen expectations, AI exacerbates the "crisis of efficiency" at sovereign levels.Conclusion: Safeguarding political independence and social identity requires a transition toward proactive policymaking and indigenous infrastructure. The study concludes that "smart regulation", developing national AI models, and enhancing algorithmic literacy are essential strategies to strengthen citizen resilience and protect data sovereignty against transnational algorithmic influence.
Background: As artificial intelligence (AI) technologies become embedded in public and private decision-making, questions of governance have become a critical global concern. The European Union (EU), widely regarded as a leader in digital regulation, has developed an AI governance architecture that includes the AI Act, Ethics Guidelines for Trustworthy AI, and multiple stakeholder platforms.Aims: This article examines how expert networks and national governance models from France, Germany, and South Africa contribute to the European Union’s artificial intelligence (AI) governance through conceptual, institutional, and procedural spillover.Methodology: The research employs comparative case study analysis, drawing on policy documents, ethical guidelines, expert reports, and process tracing to track how national frameworks migrate into EU deliberations. The theoretical framework integrates spillover theory with multi‑level governance, norm diffusion, and epistemic community perspectives.Discussion: The central question is how transnational actors influence EU regulation via mechanisms such as normative transfer, expert mobility, and platform convergence. The study hypothesizes that EU AI governance is increasingly co‑constructed through multidirectional spillover, in which norms and ethical frameworks from both the Global North and Global South are adapted and embedded into supranational regulation.Findings: South Africa’s “Fair AI” framework, France’s participatory ethics inquiry, and Germany’s strategic critique each shape EU debates on trustworthy AI, accountability, and regulatory experimentation. Together, these cases indicate that EU governance functions not as a closed, top‑down system but as a porous and adaptive architecture responsive to external influence.Conclusion: The expert communities across regions contribute to the co‑production of global AI standards, and that ethical pluralism is emerging as a significant feature of supranational regulation.
Background: Social media platforms such as Facebook, Instagram, TikTok, and X have redefined the norms of sociality, identity performance, and participation in the public sphere.Aims: This study examines how Persian-language users on X negotiate the visibility of children in online spaces through affective discourse and vernacular governance.Methodology: Analyzing 2,392 posts, we identify seven thematic formations—ranging from family blogging and sharenting to screenshot-based mockery, celebrity child cultures, and rights-based critiques. Using a hybrid methodological approach combining high-recall data retrieval, supervised multi-label topic modeling, and sentiment–intensity analysis, we map how practices like quote-tweeting and screenshotting structure public debates around parental branding, childhood agency, privacy, and consent. Central to this ecosystem is the culturally specific figure of “Arat’s father”, a discursive shorthand for the commodification of childhood under platform economies.Findings: The findings reveal a layered affective landscape where humor, outrage, and pedagogical neutrality coexist, enabling users to police age norms and negotiate ethical boundaries in real time.Conclusion: This study reveals how ordinary users in Iran and Persian-speaking contexts regulate childhood visibility through platform affordances, emotional repertoires, and normative claims. It also proposes a reproducible pipeline for analyzing culturally specific digital publics with methodological transparency and ethical sensitivity.
Background: Background: In Iran, following the introduction of modern technologies, various social groups have responded to them, among whom “Tolab” constitute one category. Due to their religious authority within Iranian society, seminarians exert both direct and indirect influence on people’s social lives.Aims: This study aims to explore how Hawzeh members engage with artificial intelligence (AI) as a manifestation of modern technology, by examining Hawzeh media such as journals and news agencies, and to explain its relationship with modernity and technological application approaches.Methodology: 122 texts from Hawzeh media over a two-year period were selected and analyzed using thematic analysis. Ultimately, three main categories were identified: “Understanding the Nature of Artificial Intelligence among Hawzeh Members”, “The Relationship between Power and Artificial Intelligence among Hawzeh Members”, and “The Operational Attention of the Hawzeh to Artificial Intelligence”.Findings: Hawzeh media perceive AI as having a variable nature, which can be utilized depending on the intention, design, and use by its users.Conclusion: The experience of the People of the Hawzeh with AI demonstrates that the systematic form of religion can also be integrated with technology as a product of modern science, because it is not entirely anti-modern, nor is it modern and subjective in the sense of defining its existence solely as a specific mode of being.
Background: Cryptocurrencies have a variety of unique qualities, from cutting-edge technology to highly secure architecture. Additionally, the ability to invest in cryptocurrency, as an asset or a function of its prosperity has made crypto-currencies attractive to venture capitalists, computer scientists, and statisticians.Aims: In this study, we concentrated on a collection of documents web-scrapped from the market section of CNBC, where each document is associated with a response variable.Methodology: These documents contain preprocessed words/terms of day-to-day reportage on cryptocurrency (Bitcoin). The corresponding response variables are the daily opening and closing price of Bitcoin prices. The Supervised Latent Dirichlet Allocation(sLDA), a statistical model of labeled documents, was used to analyze the textual data alongside their corresponding response variables, since our study aims to predict the response variable for unlabeled new documents.Results: Hidden Topics with their unique terms from the preprocessed articles were exposed through a Natural language processor. Mean absolute error (MAE), Mean absolute percentage error (MAPE), and Root mean square error (RMSE) graphs were constructed for the sLDA models with ‘k = 3,10,20,30,50,75,100 and 200 Topics’ values where the model with the best evaluation metric, was selected for prediction purpose.Conclusion: It was discovered that the sLDA model with k = 20. A posterior covariance matrix which shows the proportion of terms from the documents, making up a Topic. Coefficient values were generated in other to graphically visualize how important the discovered topics are and how they affect the market trend. Finally, the prediction of new labels (numeric-decoded closing prices) for the unlabeled documents was done and comparisons were made; the predicted labels follow a similar pattern to that of the time series closing price trend.
