• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.1
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• pp.78-88
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• 2018

The purpose of this study is to establish a utilization plan according to the cultural value of Placenta Chamber of King Sejong's Princes. We used SNS to analyze various public perceptions and opinions, collected data and analyzed it. The collection period is from June 01, 2007 to June 30, 2017 (for about 10 years), We gathered data from blogs, cafes, and Knowledge IN that contain keywords related to 'Placenta Chamber', 'Placenta Chamber of Seongju', 'Placenta Chamber of King Sejong's Princes'. and Analyzed using the text mining method of the big date program. Based on the main results of the big data analysis, Placenta Chamber's method of utilization was derived. As a result, major keywords such as King Sejong Great, Prince, Sungju, Feng Shui, culture, preservation, blessing etc were derived. The association of 'world', 'heritage', 'cultural heritage' is high, and the connection of 'Placenta Chamber', 'Gyeongsangbuk-do', 'cultural property' is high, and it was able to confirm the value of Placenta Chamber as a world cultural heritage. and It is necessary to induce visitors to feel stimulation or change of surroundings through facility refurbishment and environmental improvement around Placenta Chamber.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.408-414
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• 2018

Various studies have been conducted to reduce marine accidents. However, research on marine incidents is only marginal. There are many reports of marine incidents, but the main content of existing studies has been qualitative, which makes quantitative analysis difficult. However, quantitative analysis of marine accidents is necessary to reduce marine incidents. The purpose of this paper is to analyze marine incident data quantitatively by applying big data techniques to predict marine incident trends and reduce marine accident. To accomplish this, about 10,000 marine incident reports were prepared in a unified format through pre-processing. Using this preprocessed data, we first derived major keywords for the Marine incidents at sea using text mining techniques. Secondly, time series and cluster analysis were applied to major keywords. Trends for possible marine incidents were predicted. The results confirmed that it is possible to use quantified data and statistical analysis to address this topic. Also, we have confirmed that it is possible to provide information on preventive measures by grasping objective tendencies for marine incidents that may occur in the future through big data techniques.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.125-139
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• 2021

This study identifies the trend of Korean accounting researches on profit adjustment. We analyzed the abstract of accounting research articles published in Korean Citation Index (KCI) by using text mining technique. Among papers whose themes were profit adjustment, topics were divided into 4 parts: (i) Auditing and audit reports, (ii) corporate taxes and debt ratios, (iii) general management strategy of companies, and (iv) financial statements and accounting principles. Unlike the prediction that financial statements and accounting principles would be the main topic, auditing was analyzed as the most studied area. We analyzed topic trends based on the number of papers by topic, and could figure out the impact of K-IFRS introduction on profit adjustment research. By using Big Data method, this study enabled the division of research themes that have not been available in the past studies. This study enables the policy makers and business managers to learn about additional considerations in addition to accounting principles related to profit adjustment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.661-670
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• 2021

Research trends can be usefully used to determine the importance of research topics by period, identify insufficient research fields, and discover new fields. In this study, research trends of urban spaces, where various problems are occurring due to population concentration and urbanization, were analyzed by topic modeling. The analysis target was the abstracts of papers listed in the Korea Citation Index (KCI) published between 2002 and 2019. Topic modeling is an algorithm-based text mining technique that can discover a certain pattern in the entire content, and it is easy to cluster. In this study, the frequency of keywords, trends by year, topic derivation, cluster by topic, and trend by topic type were analyzed. Research in urban regeneration is increasing continuously, and it was analyzed as a field where detailed topics could be expanded in the future. Furthermore, urban regeneration is now becoming a regular research field. On the other hand, topics related to development/growth and energy/environment have entered a stagnation period. This study is meaningful because the correlation and trends between keywords were analyzed using topic modeling targeting all domestic urban studies.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.27-35
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• 2022

The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.71-86
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• 2023

The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.

• Korea Science and Art Forum
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• v.22
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• pp.169-183
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• 2015

As time is rapidly changing, the culture to represent an era is getting more subdivided and complex. Due to cultural diversity, the influence, cause, characteristics which could be understood in individual field centered by space in the past cannot be understood now only by the viewpoint of one field, and it has become difficult to predict and correspond to the change of the future. With the development of information and knowledge delivery system, various cultural contents to form a space are being created and lapsed, but there are a lot of parts which cannot be explained or understood by only one point of view. To inspect these situation, this study is aimed to draw the Tangibility and Intangibility Value causes that became the influence with Jongmyo Shrine, designated from UNESCO at February 1995, a traditional space with historical superiority, analyze the key factors that became the main factor to form the space, and consider the importance of the related factors. The unconstructured data technique which is applied as the method of analysis in this study can be said to be a new value judgement and viewpoint in interpreting the space. Therefore, this study is a new trial to provide a frame for multilaterally interpreting the various traditional space and culture of Korea from the past to the present.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.155-164
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• 2023

In this paper, we examine the influence of Environmental, Social, and Governance (ESG)-related content on the success of online crowdfunding proposals. Along with the increasing significance of ESG standards in business, investment proposals incorporating ESG concepts are now commonplace. Due to the ESG trend, conventional wisdom holds that the majority of proposals with ESG concepts will have a higher rate of success. We investigate by analyzing over 9000 online business presentations found in a Kickstarter dataset to determine which characteristics of these proposals led to increased investment. We first utilized lexicon-based measurement and Feature Engineering to determine the relationship between environment and society scores and financial indicators. Next, Logistic Regression is utilized to determine the effect of including environmental and social terms in a project's description on its ability to obtain funding. Contrary to popular belief, our research found that microentrepreneurs were less likely to succeed with proposals that focused on ESG issues. Our research will generate new opportunities for research in the disciplines of information science and crowdfunding by shedding new light on the environment of online micro-entrepreneurship.

• Knowledge Management Research
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• v.24 no.3
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• pp.217-237
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• 2023

Recently, in the face of successive and unexpected global economic risks, ESG(Environmental, Social, and Governance) management has risen as an essential survival strategy for businesses. Particularly, the supply chain disruptions due to the COVID-19 pandemic have added to the uncertainty of risks, heightening the importance of ESG management in the distribution industry. In this context, the role of blockchain technology in strengthening and managing the connection between the distribution industry and ESG management has become increasingly significant. While there have been extensive proposals for business models that integrate blockchain technology into distribution, few studies have specifically focused on the feasibility and effectiveness of applying blockchain to ESG management in this field. Therefore, this study analyzed the relationship between blockchain and ESG management in the distribution industry by employing association analysis, a text mining technique, on Korean academic research. Through this, the study confirmed the possibility of implementing blockchain in the distribution industry's ESG management and presented keywords to guide future research directions. The findings obtained from this study are expected to be utilized as foundational research for future studies in constructing blockchain-based business models for ESG management in the distribution industry.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.157-168
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• 2024

The frequent occurrence of structural failures at building construction sites in Korea has underscored the critical role of rigorous oversight in the inspection and management of construction projects. As mandated by prevailing regulations and standards, onsite supervision by designated supervisors encompasses thorough documentation of construction quality, material standards, and the history of any reconstructions, among other factors. These reports, predominantly consisting of unstructured data, constitute approximately 80% of the data amassed at construction sites and serve as a comprehensive repository of quality-related information. This research introduces the SL-QPA model, which employs text mining techniques to preprocess supervision reports and establish a sentiment dictionary, thereby enabling the quantification of quality performance. The study's findings, demonstrating a statistically significant Pearson correlation between the quality performance scores derived from the SL-QPA model and various legally defined indicators, were substantiated through a one-way analysis of variance of the correlation coefficients. The SL-QPA model, as developed in this study, offers a supplementary approach to evaluating the quality performance of building construction projects. It holds the promise of enhancing quality inspection and management practices by harnessing the wealth of unstructured data generated throughout the lifecycle of construction projects.