• The Journal of Information Systems
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• v.32 no.3
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• pp.151-164
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• 2023

Purpose This study aims to analyze the current status of consumer awareness on Internet banks by conducting a full investigation and collecting user opinions presented on Google Play. After cateogorizing the current dissatisfaction, we would like to present not only the direction of the Internet bank service of but also the improvements of the platform. Design/methodology/approach Using opinion mining, subjectivity analysis, polarity analysis, and polarity information analysis of comments were conducted step by step to extract negative and positive keywords. The extracted keywords analyzed the weights of the frequently appearing positive and negative keywords using the TF-IDF model. Based on previous studies that negative information is more sensitive to positive information, we tried to confirm the connection, proximity, and mediation of negative keywords. Semantic Network Analysis (SNA) was used to visualize the connection relationship between the negative comment keywords of the three Internet banks. Findings Domestic Internet banks such as Kakao Bank, K-Bank, and Toss Bank have attracted a lot of attention even before they were established, and after establishment, they have secured a wide range of users through platforms that are completely different from existing banks. This study found out that the convenience of the app affects the opening and transaction of non-face-to-face accounts, which are characteristics of domestic Internet banks, which also affects the bank's business strategy. In addition, this study shows that the business characteristics of the company can be identified.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.113-122
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• 2024

This comprehensive study delves into the analysis of user review data across various metaverse platforms, employing advanced text mining techniques such as TF-IDF and Word2Vec to gain insights into user perceptions. The primary objective is to uncover the factors that contribute to user satisfaction and dissatisfaction, thereby providing a nuanced understanding of user experiences in the metaverse. Through TF-IDF analysis, the research identifies key words and phrases frequently mentioned in user reviews, highlighting aspects that resonate positively with users, such as the ability to engage in creative activities and social interactions within these virtual environments. Word2Vec analysis further enriches this understanding by revealing the contextual relationships between words, offering a deeper insight into user sentiments and the specific features that enhance their engagement with the platforms. A significant finding of this study is the identification of common grievances among users, particularly related to the processes of refunds and login, which point to broader issues within payment systems and user interface designs across platforms. These insights are critical for developers and operators of metaverse platforms, suggesting a focused approach towards enhancing user experiences by amplifying positive aspects. The research underscores the importance of continuous improvement in user interface design and the transparency of payment systems to foster a loyal user base. By providing a comprehensive analysis of user reviews, this study offers valuable guidance for the strategic development and optimization of metaverse platforms, ensuring they remain responsive to user needs and continue to evolve as vibrant, engaging virtual environments.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.1
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• pp.50-65
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• 2024

By analyzing the style of creator avatars in the world of Metaverse, which is emerging as a fourth-generation social media platform, this study aims to identify the meta-fashion tastes of Generation Z (Gen Z) creators (born in the late 2010s and early 2020s) and to analyze the extent to which current trends in the fashion market are influencing meta-fashion. The research method uses a case study to compare meta-fashion and current fashion trends. First, five Gen Z fashion creators on ZEPETO were selected to analyze the meta-fashion styles presented by this group. In the end, a total of 100 fashion styles were analyzed by combining 50 items each from the current meta-fashion and real fashion trends. The fashion styles were found to be hip-hop, easy-casual, punk, lovely feminine, and sexy, and the main fashion items were analyzed as jeans, hip-hop style pants, sneakers, tight crop tops, dresses, tattoos, chain accessories, and dyeing. Meta-fashion is the emergence of items similar in shape to those popular in the current fashion market, but are more exaggerated or show off the human body than actual fashion items.

• Information Systems Review
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• v.25 no.2
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• pp.57-76
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• 2023

This study classifies the success of creators and YouTubers who have created channels on YouTube recently, which is the most influential digital platform. Based on the actual information disclosure of YouTubers who are in the field of science and technology category, video upload cycle, video length, number of selectable multilingual subtitles, and information from other social network channels that are being operated, the success of YouTubers using machine learning was classified and analyzed, which is the closest to the YouTube revenue structure. Our findings showed that neural network algorithm provided the best performance to predict the success or failure of YouTubers. In addition, our five factors contributed to improve the performance of the classification. This study has implications in suggesting various approaches to new individual entrepreneurs who want to start YouTube, influencers who are currently operating YouTube, and companies who want to utilize these digital platforms. We discuss the future direction of utilizing digital platforms.

• Information Systems Review
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• v.19 no.1
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• pp.123-145
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• 2017

This study empirically examines the effects of regulation on online gaming. Going beyond ad hoc heuristic approaches on individual behavior, we investigate the effects of regulation on dynamic changes of games or service providers. In particular, we propose three theoretical perspectives: social influence to investigate the regulation effect, the role of prior experience to determine the difference in the regulation effect size through users' prior experience, and network externalities to discover the difference in the regulation effect size according to the number of users on an online gaming platform. We use the vector autoregression methodology to model patterns of the co-movement of online games and to forecast game usage. We find that online gamers are heterogeneous. Therefore, policy makers should make suitable regulations for each heterogeneous group to effectively avoid generating gaming addicts without interrupting the economic growth of the online gaming industry.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of Korean Library and Information Science Society
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• v.46 no.2
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• pp.337-366
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• 2015

This study had begun about the conflict between a lack of social adjustment and integration program for resident foreigners in Korea and a duplication of multicultural service in a specific area. This study was implemented through literature review and interview for analyses of the current status and problems of multicultural policy, subdivided into 3-stages model to reach the multiculturalism as multicultural policy process. The first stage suggested the unification of a channel for establishing a policies, reinforcing the functions of government ministries and the cooperation between the branches of the government. The second stage attempted to build the multicutural institutes network in a specific area unit, considering of the geographical and administrative environments. The third stage focused on the activities of individual organizations and proposed collaboration with library, school, support center for multi-cultural families, social service center, sport center, community center, and cultural facility. Additionally, 3-stages model emphasized on civic organization's role. This study was offered a meta-platform leaded by library community for sharing the information about planning and managing of multicutural programs and also mentioned significances for formulating multicutural policies. As a result, this study was presented and specified the 3-stages model to reach the multiculturalism, and verified the various considerations which have influenced the refinements of the multicultural policies as the demographic and geographical characteristics.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.87-107
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• 2016

Understanding market convergence has became essential for small and mid-size enterprises. Identifying convergence items among heterogeneous markets could lead to product innovation and successful market introduction. Previous researches have two limitations. First, traditional researches focusing on patent databases are suitable for detecting technology convergence, however, they have failed to recognize market demands. Second, most researches concentrate on identifying the relationship between existing products or technology. This study presents a platform to identify the opportunity of market convergence by using product databases from a global B2B marketplace. We also attempt to identify convergence opportunity in different industries by applying Structural Hole theory. This paper shows the mechanisms for market convergence: attributes extraction of products and services using text mining and association analysis among attributes, and network analysis based on structural hole. In order to discover market demand, we analyzed 240,002 e-catalog from January 2013 to July 2016.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.305-313
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• 2021

This study collected and analyzed big data from 1995 to 2020, focusing on the keywords "unwed mother", "single mother," and "single mom" to present appropriate government support policy directions according to changes in perspectives on unwed mothers. Big data collection platform Textom was used to collect data from portal search sites Naver and Daum and refine data. The final refined data were word frequency analysis, TF-IDF analysis, an N-gram analysis provided by Textom. In addition, Network analysis and CONCOR analysis were conducted through the UCINET6 program. As a result of the study, similar words appeared in word frequency analysis and TF-IDF analysis, but they differed by year. In the N-gram analysis, there were similarities in word appearance, but there were many differences in frequency and form of words appearing in series. As a result of CONCOR analysis, it was found that different clusters were formed by year. This study confirms the change in the perspective of unwed mothers through big data analysis, suggests the need for unwed mothers policies for various options for independent women, and policies that embrace pregnancy, childbirth, and parenting without discrimination within the new family form.

• The Korean Society of Law and Medicine
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• v.21 no.2
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• pp.3-33
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• 2020

Until recently the German and the South Korean medical associations reacted cautiously to the introduction of telemedicine between doctor and patient which is exclusively on the platform conducted. But the General Assembly of German Physicians voted to lift the ban on remote treatment with the amendment to Section 7 (4) MBO-Ä(Medical Association's Professional Code of Conduct) in 2018 and the situation has been fundamentally changed in Germany. From then until now 16 of 17 rural medical associations have changed their professional code to allow telemedicine. In addition the legislature started to prepare the basis for the introduction of the electronic health card (eGK) and the telematics infrastructure. So far, various laws such as Medicinal Products Act, Drug Advertisement Act and Social Code have been changed to support legalization of telemedicine and digitalization of health care. Unlike in Germany, the social circumstances such as excessive centralization of the big hospitals in Seoul and the resulting concern of small medical practices for profitability are the main obstacles to the introduction of telemedicine. However the German approach how to legalise the telemedicine and to prepare for legal and technical infrastructure is also interesting in South Korea. The discussions for and against the changes in the law and the telematics infrastructure attempted by the German government for several years indicate that not only lifting the ban on remote treatment, but also harmonization of all the related legal system could guarantee successful implementation of telemedicine.