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All Journal Language, Technology, and Social Media
Georgios P. Georgiou
University of Nicosia
Humanities Education Languange, Linguistic, Communication & Media Social Sciences

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Mapping The Ethical Discourse in Generative Artificial Intelligence: A Topic Modeling Analysis of Scholarly Communication Georgios P. Georgiou
Language, Technology, and Social Media Vol. 3 No. 2 (2025): December 2025 | Language, Technology, and Social Media
Publisher : WISE Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70211/ltsm.v3i2.230

Abstract

As generative artificial intelligence (GenAI) continues to reshape numerous sectors, the ethical implications of its deployment have become a critical area of society. This study employs a topic modeling technique to systematically analyze a large corpus of peer-reviewed literature related to ethics in GenAI, aiming to uncover prevailing themes and conceptual patterns. Using a natural language processing method, the analysis identified ten distinct topics that were subsequently synthesized into six overarching macrotopics related to ethics in GenAI: (1) education and learning, (2) bias, frameworks, and legal compliance, (3) cybersecurity, governance, and risks, (4) social impact and sustainability, (5) digital transformation and emerging tech, and (6) academic research and writing. Each macrotopic is examined through the lens of existing scholarly literature, providing an overview of current debates in the area. The findings demonstrate the pressing need for comprehensive governance frameworks that prioritize transparency, fairness, and accountability in the development and deployment of GenAI systems. The relevance of the emerging macrotopics extends beyond technical or policy considerations, situating them within broader ethical discourse around language, communication, and media technologies, where questions of authorship, representation, and discursive power are increasingly mediated by GenAI. By mapping the evolving ethical landscape of GenAI, this study contributes to a more informed and critical understanding of how to align technological innovation with societal values and legal norms.
Occupational Noise Exposure and Age as Predictors of Disabling Hearing Loss in Pakistan Huma Hanif; Ibtasam Thakur; Georgios P. Georgiou; Paris Binos
Language, Technology, and Social Media Vol. 4 No. 1 (2026): January–March 2026
Publisher : WISE Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70211/ltsm.3026-7196.275

Abstract

This study aimed to assess the prevalence, severity, and functional impact of hearing loss (HL) in Rawalpindi and Islamabad, Pakistan. A total of 400 participants, aged 12 to 70 years, were enrolled in the study, and data were collected using pure-tone audiometry (PTA) and the Hearing Handicap Inventory for Adults (HHIA). The results indicated that 18% of participants had some form of HL, with 22% meeting the criteria for disabling HL (≥35 dB HL). The severity of HL ranged from mild to profound, with 55% of participants exhibiting no measurable HL. Sensorineural HL was the most common type (60%), followed by conductive (24%) and mixed (10%) types. Bivariate analysis revealed that older age (≥60 years) and occupational noise exposure were significantly associated with HL ≥35 dB HL. The multivariable logistic regression model confirmed that age and occupational noise exposure were independent predictors of HL. Furthermore, hearing aid users reported significantly lower HHIA scores, indicating reduced psychosocial burden compared to non-users. This study highlights the need for early detection, public health interventions, and increased access to hearing aids, particularly in rural areas. The findings also demonstrate the importance of occupational noise control and workplace interventions to reduce the risk of HL in high-noise environments. The study contributes to the understanding of HL in Pakistan, offering valuable insights for improving hearing care accessibility and policy development.
Co-Authors Huma Hanif Ibtasam Thakur Paris Binos