- P-ISSN1738-6764
- E-ISSN2093-7504
- KCI
ISSN : 1738-6764
Vol.21 No.3
Abstract
Stress can arise even with the effective use of a product, and it can cause negative emotions and affect the mind and body in different ways. This study focuses on stress caused by interacting with digital products and which specific elements of user interfaces could induce stress and result in its known negative consequences. Previous studies and cases discussing some relation between user interfaces and stress were reviewed to identify elements that could cause stress to users while interacting with digital products. After merging similar and overlapping concepts, eleven final stress-inducing elements associated to 4 different categories (User Experience, Usability, Psychophysiology of Stress and Interface Visual Design) were identified, defined and exemplified: Content Overload, Service Instability, Low level of Attractiveness, Lack of Control, Low level of Safety, Low Usability, Unpredictability, Uncertainty, Unfamiliarity, Judgment or social evaluation threat and Poor Visual Design. This set of elements could help design better interfaces while taking into consideration users’ mental and emotional state.
Abstract
This research investigates the implementation and effectiveness of Domain Name System Security Extensions (DNSSEC) in conjunction with Bettercap for mitigating Man-in-the-Middle (MITM) attacks in network environments. Through a comprehensive virtual lab demonstration, we examine the vulnerabilities in traditional Domain Name System (DNS) and evaluate how DNSSEC’s cryptographic signing mechanisms enhance security. The study employs Bettercap as both an attack simulation tool and a monitoring platform to demonstrate real-world MITM attack scenarios and their prevention. Our experimental setup includes multiple virtual machines configured to simulate various network topologies, allowing for controlled testing of DNSSEC implementation against common attack vectors. Results demonstrate that effective DNSSEC deployment notably decreases vulnerability to DNS spoofing and MITM attacks, achieving substantial success in detecting and preventing unauthorized DNS record modifications. The study also highlights implementation challenges and offers practical recommendations for network administrators. This work contributes to the growing body of knowledge on DNS security and offers empirical evidence supporting the adoption of DNSSEC in modern network infrastructures.
Abstract
The study aims to investigate the association between maternal parenting stress and children’s internet addiction, with achievement pressure perceived by children as a mediator, and explore the moderating role of maternal social support employing Abidin’s Parenting Stress Model. Data from the thirteenth Panel Study on Korean Children were utilized, focusing on the responses of 12-year-old children (N=1,118) for secondary analysis. Using SPSS 26.0 and Process macro 4.2, the indirect path (Model 4) and the moderated mediation hypothesis (Model 7) were tested within a cross-sectional design. We found that maternal parenting stress and achievement pressure perceived by children had a significant positive direct effect on children’s internet addiction. Also, achievement pressure perceived by children partially mediated the relationship between maternal parenting stress and children’s internet addiction. The moderated mediation effect of maternal informational support was significant in the relationship between maternal parenting stress, achievement pressure perceived by children, and children’s internet addiction. When the level of maternal informational support was high, the direct and indirect effect of maternal parenting stress on children’s internet addiction was lowered. To prevent children’s internet addiction, it is crucial to understand maternal parenting stress, achievement pressure perceived by children, and the level of maternal social support. The adverse effect of maternal parenting stress and achievement pressure perceived by children on children’s internet addiction can be mitigated through the provision of maternal social support. In particular, providing informational support for mothers, such as university admission trends and effective parenting styles is crucial for reducing maternal parenting stress.
Abstract
On streaming platforms with vast and diverse content, digital advertising—especially via social media—has become increasingly important alongside traditional promotional methods in movie marketing. Grounded in Dual Coding Theory, we hypothesize that congruence between visual elements (e.g., posters) and verbal elements (e.g., synopses) in digital ads positively affects advertising effectiveness. Prior research has largely relied on subjective human judgments to assess image–text congruence, limiting measurement objectivity. This study proposes a data-driven, objective approach to measuring image–text congruence and empirically examines its impact on customer engagement. Using IMDb data, we employed LLaVA, a multimodal model, to generate textual descriptions of movie poster images and computed cosine similarity between these descriptions and the corresponding synopses, thereby operationalizing an image–text congruence score. Extending the Theory of Cognitive Consistency, we also test the effects of consumer–ad imagery congruence and brand–ad congruence on brand evaluations, incorporating image–text congruence as a key factor. The importance of image–text congruence is further validated via variable-importance analyses from machine-learning models and a consumer survey. Based on these findings, we offer theoretical and practical implications for optimizing movie marketing strategies and enhancing customer engagement.
Abstract
The Fourth Industrial Revolution, driven by digital innovations, has brought significant changes to core technologies, industrial systems, and job structures. Against this backdrop, this study explores the application of AI image generation models, specifically those based on diffusion architectures, in the development of picture book illustrations. Focusing on two widely adopted tools—DALL·E 3 and Midjourney—which represent state-of-the-art implementations of diffusion-based image synthesis, the study adopts a case study approach to evaluate their stylistic characteristics, usability, and associated challenges. The research compares the visual styles generated by both tools, outlines a five-stage workflow for AI-assisted picture book creation, and analyzes limitations in AI creativity, data bias, and ethical concerns. Findings indicate that DALL·E 3 produces whimsical and intuitive illustrations suitable for narrative clarity, while Midjourney excels in artistic expression and visual depth. By highlighting the capabilities and constraints of these AI models, this study offers practical insights into how such technologies can support creative illustration processes. It also emphasizes the need for further research using objective data and statistical methods to assess user satisfaction and broader applicability.
Abstract
This study examines YouTube videos as a key medium for disseminating policy issues, specifically focusing on the controversy surrounding the expansion of medical schools in Korea. By analyzing video titles and user engagement metrics—such as views, likes, and comments—the research explores how sentiment and framing affect the spread of policy discourse. YouTube was chosen for its status as the most influential platform in Korea for discussing policy matters, along with its unique capacity to measure user engagement through video content and an algorithm-driven recommendation system. The findings reveal three critical insights: (1) the need to restore credibility in policy communication, (2) the significant impact of risk-oriented discourse in fostering public engagement, and (3) the paradoxical resurgence of traditional media's influence as issues become increasingly complex. The study also proposes a model for issue dissemination on YouTube, providing valuable insights for both media and policy research.
Abstract
This study explores the potential of LLM-based AI assistants to alleviate labor shortages in East Asia, with a focus on South Korea, by attracting foreign workers. Previous research indicates that AI assistants can enhance job performance and adaptability. Through case studies and semi-structured interviews with a unique sample of seven foreign workers in South Korea who utilize AI assistants in their roles, along with three local colleagues, this study reveals that the advantages of AI assistants are particularly pronounced among foreign employees. All participants noted that AI assistants significantly improved communication and translation, leading to enhanced job performance and adaptability. The findings suggest that AI was beneficial across all levels of Korean language proficiency, with those possessing lower proficiency relying on it more heavily. The study advocates for further research to quantitatively validate these results, especially concerning foreign workers in other multilingual environments.
Abstract
Since the 1980s, the active participation of domestic broadcasting companies in producing Korean documentaries has significantly transformed the field. This shift has led to the creation of programs that explore a wide range of local topics, establishing documentaries as essential tools for conveying knowledge and cultural values. The advent of digital technology has further changed the visual presentation of documentaries, enabling the integration of computer graphics (CG) and animation. These innovations have made complex scientific concepts, historical events, and intricate information more accessible and understandable, thereby enhancing their educational function. This study examines the impact of digital technology, particularly CG, on Korean documentary production since the 1980s. It explores how CG has been employed for information delivery and historical representation, improving both the viewing experience and the social role of documentaries. With advancements in CG and virtual studios, documentaries have evolved from simple records into immersive visual experiences that amplify their social impact. This paper highlights how these technological advancements have transformed documentaries into powerful mediums for education and cultural storytelling, thereby increasing their influence and value in society.
Abstract
This study critically examines the representation of feminism in recent Oscar-winning films and explores how these depictions reflect broader power dynamics within cultural institutions. Although the Academy Awards have increasingly showcased "strong female" characters, a deeper analysis reveals that these portrayals often remain confined by traditional male-dominated narrative frameworks. Drawing on Foucault’s theory of disciplinary power and feminist epistemology, informed by feminist standpoint theory, this research argues that the construction of female subjectivity in these films frequently reinforces existing power structures rather than deconstructing them. By analyzing characters in films such as CODA, Everything Everywhere All at Once, Minari, and Poor Things, the study highlights how female characters are often positioned as reflections or reversals of male roles, failing to achieve genuine feminist ideals. To ensure analytic consistency, the analysis is organized around four dimensions—agency, emotional labor, institutional endorsement, and narrative closure—while employing a working definition of “internalized discipline” to differentiate between surface progress and structural transformation. Publicly available institutional summaries are used solely as contextual materials, and claims are limited to analytic generalizations.
Abstract
This study empirically examined the impact of COVID-19 on alcohol-related issues within the community. The findings reveal three key points: First, increased stress levels among community members contributed to a rise in alcohol consumption. Second, COVID-19 restricted access to hospital services for alcohol-related patients, leading to approximately 50% of these patients discontinuing their hospital visits. This limitation worsened the conditions of alcohol-dependent individuals; those who sought hospital care for the first time after the pandemic experienced emergency room visit rates that were 14 times higher and hospitalization rates that were 47 times higher. Third, the negative effects of COVID-19 were more pronounced among women than men. This study supports previous research showing that pandemic crises result in increased alcohol consumption and reduced access to medical services. It also underscores the necessity of enhancing tele-mental health services and essential in-person treatments. However, since the study relies on data from a single regional hospital, its generalizability is limited. Future research should include nationwide analyses and explore the reasons behind the decline in hospital visits among alcohol-related patients.
Abstract
The purpose of this study is to compare the performance of two Korean-to-English machine translations of Pachinko: ChatGPT-3.5 (ChatGPT) and Naver Papago (Papago). The drama dialogues were analyzed based on 590 pairs of samples translated using both ChatGPT and Papago to identify translation accuracy as well as lexical, grammatical, omission, and mechanical errors. These errors were further categorized into 11 subtype error patterns. The research found that ChatGPT produced 343 correct instances (58.1%) out of 590 attempts, while Papago achieved 223 correct translations (37.8%) for the same dataset. With regard to the four categories examined in this study, ChatGPT generated 190 lexical errors, 31 grammatical errors, 18 omissions, and 8 mechanical errors. In contrast, Papago yielded 301 lexical errors, 48 grammatical errors, 10 mechanical errors, and 8 omissions. Among the 11 error subtypes, the most frequent were incorrect word meaning errors, with 148 instances for ChatGPT and 226 for Papago, followed by pronoun errors, observed in 23 instances for ChatGPT and 40 for Papago. This comprehensive analysis of the primary error classifications reveals limitations in both ChatGPT and Papago. These findings underscore the need for future updates to enhance sensitivity to the unique aspects of the Korean language in both translation systems.
Abstract
Max Weber’s Collected Works (Max Weber-Gesamtausgabe) in German were fully published in 2020. The volumes include 34713,471 letters written and sent by Max Weber between 1875 toand 1920. TheThese publications posepresent several challenges to Weber’s scholarship due to the language barrier and the hundred yearcentury-long interval between Weber’s demisedeath and the publicationrelease of his collected works. Against this backdrop, this article applies novel network analysis tools to explore the relationshiprelationships between Weber and his correspondents. With the complete collection of his letters now available to Weberian scholars, we have undertaken an innovative project that integrates data science into this field. To achieve this, we haveWe extracted metadata from Weber’s Collected Works to construct network data. We employed, employing R and various R packages to applyfor network analysis and data visualization. Additionally, we also providedhave made the dataset and R scripts available online as open-access resources to facilitate reproducibility. As we employ onlyWhile our research relies solely on statistical analysis of Weber’s letters without qualitative examination, the scope of our research could be considered limited. Nevertheless, we feel our researchwe believe it makes a meaningful contribution to Weberian studies. By academically exploring the Collected Letters, this study isrepresents a pioneering effort with significant implications, encouraging further research and scholarship in the field.
Abstract
This study empirically analyzes the impact of the robotics industry on national competitiveness and the labor market. Utilizing panel data from 43 countries between 1999 and 2022, we investigate how the adoption of robotics influences national and industrial productivity, employment levels, and job quality. The findings reveal that new robot adoption significantly boosts productivity in both robot-leading and robot-following countries. However, while robot density positively affects productivity in robot-leading countries, it negatively impacts productivity in robot-following countries, likely due to challenges in technological adaptation. In terms of employment, new robot adoption fosters job growth in robot-following countries but leads to job losses in robot-leading countries, reflecting differences in industrial maturity. Robot density generally decreases employment in both groups, indicating job displacement driven by automation. Regarding job quality, the effect is minimal in robot-leading countries due to labor market adaptability. Conversely, in robot-following countries, initial robot adoption tends to lower job quality, although increased robot density improves it over time through productivity gains. These findings underscore how the economic and labor impacts of robotics adoption differ based on a country’s level of industrial development and labor market structure. This study provides empirical evidence to guide policies on robotics utilization, workforce adaptation, and strategies to enhance industrial competitiveness.
Abstract
This study presents an adaptive English text regeneration system that modifies authentic materials to match learners' CEFR (Common European Framework of Reference for Languages) proficiency levels (A1–C2). It addresses the crucial challenge of accessibility while maintaining the original meaning. Leveraging advancements in large language models (LLMs), our framework employs a three-phase process: first, CEFR-based text analysis utilizing curated vocabulary lists and syntactic metrics; second, multi-level regeneration through the fine-tuned Qwen 2.5 model; and third, rigorous validation of semantic fidelity (achieving a 92% BERT score) and readability. Experimental results with 300 learners indicate significant improvements, with a 32% increase in comprehension for beginner groups and a 25% increase for intermediate groups. Additionally, there is a 40% decrease in self-reported anxiety. The system's real-time processing capability (under 3 seconds per page) ensures practical scalability.Our work makes three key contributions: it establishes the first comprehensive framework covering all six CEFR levels with empirical validation; it integrates pedagogical and psychological principles to boost learner motivation and reduce anxiety; and it demonstrates the effectiveness of progressive complexity scaffolding while setting actionable benchmarks for LLM-driven educational tools. By balancing linguistic precision with psychological benefits—such as increased motivation and confidence—the system enhances the role of AI in language education. Future research will focus on adapting colloquial language and examining longitudinal impacts on knowledge retention, further bridging the gap between authentic content and learner needs.
Abstract
As global populations age, interest in well-being, beauty, and health enhancement has increased, leading to growth in the home beauty device market. This study investigates the economic impacts of the home beauty device industry in Korea by employing an exogenous demand-driven model based on the latest 2020 Input-Output (IO) table. The analysis reveals that the home beauty device industry generates a production-inducing effect of 1.7078 KRW and a value-added creation effect of 0.9352 KRW for additional 1 KRW increase in industry output. Moreover, the industry is associated with employment- and labor-inducement effects of estimated 5.4240 and 4.4589 persons, respectively, for every 1 billion KRW increase in output. However, the inter-industry linkage effects, encompassing both forward and backward linkages, are relatively small compared to other industries. These findings provide valuable quantitative insights for policymakers and stakeholders to help develop strategic initiatives that support and enhance the growth potential of Korea’s home beauty device industry.