• Knowledge Management Research
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• v.23 no.4
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• pp.315-338
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• 2022

In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.10
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• pp.753-762
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• 2019

It is very important to use the raw material in a particular field of research or education. Research without raw materials are difficult to prove and often remain hypothesis. The use of the raw material is also important in area studies that study specific areas. However, research of area studies, especially Western history, raw material and historical archives are very important data, but it is difficult to obtain and refer to these data due to physical or spatial constraints. In order to solve this problem, there is a method of collecting and providing historical archives, but it is currently difficult to find a case of providing overseas historical archives as a web system in Korea. Accordingly, in this paper proposes the necessity of collecting historical archives, the method of collection, and the method of digital archiving of collected data structurally and systematically. In this regard, investigate the existing research cases on the archive system and database design, and it description the differentiation between the existing systems and the modeling method proposed in this study. Also, to improve the efficiency of the search, it proposes a method of adding a tag table when database modeling.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1869-1880
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• 2021

Korean Journal of Remote Sensing (KJRS), leading the field of remote sensing and GIS in South Korea for over 37 years, has published interdisciplinary research papers. In this study, we performed the topic modeling based on Latent Dirichlet Allocation (LDA), a probabilistic generative model, to identify the research topics and trends using 1) the whole articles, and 2) specific articles related to natural and environmental disasters published in KJRS by analyzing titles, keywords, and abstracts. The results of LDA showed that 4 topics('Polar', 'Hydrosphere', 'Geosphere', and 'Atmosphere') were identified in the whole articles and the topic of 'Polar' was dominant among them (linear slope=3.51 × 10^-3, p<0.05) over time. For the specific articles related to natural and environmental disasters, the optimal number of topics were 7 ('Marine pollution', 'Air pollution', 'Volcano', 'Wildfire', 'Flood', 'Drought', and 'Heavy rain') and the topic of 'Air pollution' was dominant (linear slope=2.61 × 10^-3, p<0.05) over time. The results from this study provide the history and insight into natural and environmental disasters in KRJS with multidisciplinary researchers.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.873-885
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• 2022

The particulate matter (PM) has emerged as a hot topic around the world as it has been reported that PM is related to an increase in mortality and prevalence rates. In South Korea, the importance of PM has been recognized since the late 1990s, and various studies on PM have been conducted. This study investigated the PM research topics and trends for papers (D=2,764) published in Research Information Sharing Service (RISS) using topic modeling based on Latent Dirichlet Allocation (LDA). As a result, a total of 10 topics were identified in the whole papers, and the PM research topics were classified as 'PM reduction (Topic 1)', 'Government policy and management (Topic 2)', 'Characteristics of PM (Topic 3)', 'PM model (Topic 4)', 'Environmental education (Topic 5)', 'Bio (Topic 6)', 'Traffic (Topic 7)', 'Asian dust (Topic 8)', 'Indoor PM (Topic 9)', 'Human risk (Topic 10)'. In particular, the proportion of papers on topics 'Government policy and management (Topic 2)', 'PM model (Topic 4)', 'Environmental education (Topic 5)', and 'Bio (Topic 6)' to the toal number of papers increased over time (linear slope > 0). The results of this study provide the new literature review methodology related to particulate matter and the history and insight.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.515-536
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• 2022

The purpose of this study is to understand the content characteristics in YouTube videos of the National Archives of Korea. For this purpose, keywords, video data, and viewer responses were collected for 324 videos posted by the National Archives of Korea for five years since April, 2017. Social network analysis, topic modeling, and content analysis were performed. Based on this, the main keywords leading the YouTube videos of the National Archives of Korea, 7 major topics and 20 sub-topics were identified. The characteristics of the YouTube videos and keywords network were studies. In addition, video characteristics were analyzed as external characteristics, video editing and delivery methods, and content characters. The study found that the YouTube channel of the National Archives of Korea has been posting the videos related to various topics such as places, history, and events as well as the basic functions of the archives to induce viewers' interest in the archives. The study also identified the areas that needed to be improved such as low response from viewers, lack of content that could interest viewers, and lack of channel operation to interact or communicate with viewers. Finally, the study was concluded with a proposal to spread the videos of the National Archives of Korea to more users.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.207-235
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• 2022

In a knowledge-based society where knowledge and information industries are the main pillars of the economy, knowledge sharing and diffusion and its systematic management are recognized as essential strategies for improving national competitiveness and sustainable social development. In the field of Information Systems (IS) research, where the convergence of information technology and management takes place in various ways, the evolution of knowledge occurs only when researchers cooperate in turning old knowledge into new knowledge from the perspective of the scientific knowledge network. In particular, it is possible to derive new insights by identifying topics of interest in the relevant research field, applied methodologies, and research trends through network-based interdisciplinary graftings such as citations, co-authorships, and keywords. In previous studies, various attempts have been made to understand the structure of the knowledge system and the research trends of the relevant community by revealing the relationship between research topics, methodologies, and co-authors. However, most studies have compared two or more journals and been limited to a certain period; hence, there is a lack of research that looked at research trends covering the entire history of IS research. Therefore, this study was conducted in the following order for all the papers (from its first issue in 1977 to the first quarter of 2022) published in the MIS Quarterly (MISQ) Journal, which plays a leading role in revealing knowledge in the IS research field: (1) After extracting keywords, (2) classifying the extracted keywords into research topics, methodologies, and theories, and (3) using topic modeling and keyword network analysis in order to identify the changes from the beginning to the present of the IS research in a chronological manner. Through this study, it is expected that by examining the changes in IS research published in MISQ, the developing patterns of IS research can be revealed, and a new research direction can be presented to IS researchers, nurturing the sustainability of future research.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.2
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• pp.145-152
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• 2015

In the study, the effects of damping devices on damping ratio increase and wind-load reduction were investigated based on the computational platform, which is one of the parametric modeling methods. The computational platform helps the designers or engineers to evaluate the efficacy of the numerous alternative structural systems for irregular Super-Tall building, which is crucial in determining the capacity and the number of the supplemental damping devices for adding the required damping ratios to the building. The inherent damping ratio was estimated based on the related domestic and foreign researches conducted by using real wind-load records. Two types of damping devices were considered: One is inter-story installation type passive control devices and the other is mass type active control devices. The supplemental damping ratio due to the damping devices was calculated by means of equivalent static analysis using an equation suggested by FEMA. The optimal design of the damping devices was conducted by using the computational platform. The structural element quantity reduction effect resulting from the installation of the damping devices could be simply assessed by proposing a wind-load reduction factor, and the effectiveness of the proposed method was verified by a numerical example of a 455m high-rise building. The comparison between roof displacement and the story shear forces by the nonlinear time history analysis and the proposed method indicated that the proposed method could simply but approximately estimate the effects of the supplemental damping devices on the roof displacement and the member force reduction.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.156-164
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• 2021

Currently, digital restoration has s long way to go. Character restoration is only used as a one-time event to restore the shape of a specific person, and building restoration is only composed of digital modeling rather than using the restored cultural assets as content. There is a limit to restoring even the story of a building or a person with the current restoration method alone. Therefore, this study analyzed the method and process of digital restoration of a 'historical and cultural space' encompassing spaces, people, and events, focusing on relationships. In order to derive digital restoration methods, the case of 'Latelier', an indoor theme park based on Gogh, was analyzed. According to the study, the relationship of the person important for digital restoration is important. Based on Gogh's relationship, the process was formalized in four stages for digital restoration: the preparation stage, the digital archive stage, the DB advancement stage, and the demonstration stage. The restoration of the story of the character through the relationship can be expected to converge the past and the present as a true historical restoration, and through this, it is expected that the innovative development of digital restoration can be achieved.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.3
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• pp.366-379
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• 2015

Objectives: The objective of this study is to assess airborne particulate matter(PM) pollution and its effect on health of residents living near Ansim Briquette Fuel Complex in Daegu metropolitan region. Methods: The California Puff(CALPUFF) dispersion model, version 5.8, which can estimate the dispersion direction and range of airborn $PM_{10}$ was used to determine the possible areas affected by $PM_{10}$ pollutants emitted from Ansim briquette fuel complex. The CALPUFF modeling with 200 m grid-cell resolution was performed based on $PM_{10}$ emissions estimated from the amount of coal consumption in the fuel complex for four months in 2012. The Weather Research and Forecasting(WRF) fields were processed using CALMET to produce CALPUFF-ready meteorological inputs. Also, the distance from Ansim Briquette Fuel Complex to the residence of each environmental pneumoconiosis patient was analyzed. In addition, the affecting region of the pollutants emitted from briquette factories in Ansim Briquette Fuel Complex was determined. Results: CALPUFF modeling results showed that the highest concentrations of $PM_{10}$ were found near around the fuel complex. The modeled $PM_{10}$ distributions were characterized by significant decreases in concentration with distance from the complex. Seasonally, the highest concentration of $45{\mu}g/m^3$ was calculated in October which was mostly due to the distinct variation of amount of emission. Additional modeling with the maximum $PM_{10}$ emission of about 88 tons per year in 1986 showed that the highest concentration in October was nearly increased by 8 times than the concentration modeled with emission of 2010. As a result of medical examination and interviews for the residents in Ansim Briquette Fuel Complex and its surroundings, 8 environmental pneumoconiosis patients were found. These patients do not have occupational exposure and history. These patients have lived 0.3~1.1 km area in Ansim Briquette Fuel Complex and its surroundings. Conclusions: Airborne particles emitted from Ansim Briquette Fuel Complex can contribute to significant increase in $PM_{10}$ concentration in residential areas near around the complex. Especially, the residents near fuel complex may exposed to the pollutants emitted from the factories in Ansim Briquette Fuel Complex.