• 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 Environmental Impact Assessment
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• v.32 no.6
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• pp.556-576
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• 2023

This study attempted to find a way to utilize idle spaces in rural areas as a way to respond to rural extinction. Based on the keywords "startup," "youth start-up," and "youth start-up+rural," start-up+rural," the study sought to identify the perception of idle facilities in rural areas through the keywords "Idle facilities" and "closed schools." The study presented basic data for policy direction and plan search by reviewing frequency analysis, major keyword analysis, network analysis, emotional analysis, and domestic and foreign cases. As a result of the analysis, first, it was found that idle facilities and school closures are acting importantly as factors for regional regeneration. Second, in the case of youth startups in rural areas, it was found that not only education on agriculture but also problems for residence should be solved together. Third, in the case of young people, it was confirmed that it was necessary to establish digital utilization for agriculture by actively starting a business using digital. Finally, in order to attract young people and revitalize the region through best practices at home and abroad, policy measures that can serve as various platforms such as culture and education as well as startups should be presented in connection with local residents. These results are significant in that they presented implications for youth start-ups in rural areas by reviewing start-up recognition for the influx of young people as one of the alternatives for the use of idle facilities and regional regeneration, and if additional solutions are presented through field surveys, they can be used to set policy goals that fit the reality.

• 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.

• Journal of Environmental Impact Assessment
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• v.27 no.1
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• pp.92-104
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• 2018

The loss of biodiversity has become a global issue. In order to cope with this problem, national biodiversity strategies and action plan (NBSAP) at national level as well as local biodiversity strategies and action plan (LBSAP) at local level have been established in many countries. In this study, we analyzed 8 domestic LBSAPs and 41 foreign LBSAPs through semantic network analysis to investigate the characteristics of domestic and foreign LBSAPs. The results showed that conservation and management were the most used keywords in both domestic and foreign LBSAPs but the ranking of other keywords used in vision, goal, strategy, and action plan sector was different. Thus, it has been found that there is a difference between domestic and foreign practical approaches to conservation and management of biodiversity. Results of the network analysis showed that the domestic network has a more detailed distributed network, while the foreign network has a more comprehensive and integrally configured dense network. These differences may be due to differences of threats to biodiversity, problem recognition, or differences in local circumstances. These results are expected to help establish LBSAP in other region or to assess the local roles to achieve the strategic goals of the Convention on Biological Diversity.

• 재활복지
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• v.20 no.4
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• pp.157-175
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• 2016

The purpose of this study was to analyze the perceptions of disabled sports that were reported the newspapers using semantic network analysis method. for this purpose, 745 news articles were selected from 21 source in Naver news searching engine. The main keyword for searching on newspapers was 'disabled sports'. Krkwic software was used for keyword cleansing and co-occurrence of text to text matrix in frequencies. Centrality indices that are degree, between and eigenvector, were used to analyze the perceptions of disabled sports from Netminer 4.0 for semantic network analysis. The conclusion of overall results from this study are follows; First, the core keyword of disabled sports in newspapers are 'impression', 'challenge', 'festival', 'dream' and hope. And there is different concepts of cognition among types of disability. Second, there are two elements on the perceptions of disabled sports from reported newspapers; sports performance and emotional. Specifically, main stream of keyword were 'Paralympics' and 'Special Olympics' on sports performance element and 'impressive' and 'challenge' in emotion element.

• Korean journal of communication and information
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• v.43
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• pp.314-358
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• 2008

This study examined how the meaning of news stories covering the split of national opinion was constructed in the media to represent social conflicts. To clarify the function of the term 'split of national opinion' as an ultimate term, this study examined the meaning of the term in the context of both text and society. Ten newspapers were included in the content analysis. The frequency of words used for the purpose of metaphor and equivalent in describing the split of national opinion was calculated to determine their meaning in the textual context. The frequency of incidents and subjects involved in allegedly causing the split of national opinion was calculated to determine their meaning in the social context. The results of this study are summarized as follows: First, the term 'split of national opinion' was coined by the newspapers as a metaphor of disease, disaster, and cost. The attitudes or the ways in which the split of national opinion was dealt with were generally negative and passive. Second, the term 'split of national opinion' was dealt with an equivalent status of such terms as national policy, national loss, societal problems, and ideology. Third, each newspaper reported that the split of national opinion had been caused by certain subjects, which indicates that each newspaper had its own position of viewing who was the key player in splitting the national opinion. The implication was also discussed that the use of the ultimate term would incur the unbalance of power between participants and the existing players, which would make individuals or groups who were involved in the social actions excluded and make the newspapers exercise the rhetorical power as news media.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.139-155
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• 2016

The purpose of this study is to find the research identity of the Korea Intelligent Information Systems Society through the profiling methods and co-word analysis in the most recent three-year('2014~'2016) study to collect keyword. In order to understand the research identity for intelligence information system, we need that the relative position of the study will be to compare identity by collecting keyword and research methodology of The korea Society of Management Information Systems and Korea Association of Information Systems, as well as Korea Intelligent Information Systems Society for the similar. Also, Korea Intelligent Information Systems Society is focusing on the four research areas such as artificial intelligence/data mining, Intelligent Internet, knowledge management and optimization techniques. So, we analyze research trends with a representative journals for the focusing on the four research areas. A journal of the data-related will be investigated with the keyword and research methodology in Korean Society for Big Data Service and the Korean Journal of Big Data. Through this research, we will find to research trends with research keyword in recent years and compare against the study methodology and analysis tools. Finally, it is possible to know the position and orientation of the current research trends in Korea Intelligent Information Systems Society. As a result, this study revealed a study area that Korea Intelligent Information Systems Society only be pursued through a unique reveal its legitimacy and identity. So, this research can suggest future research areas to intelligent information systems specifically. Furthermore, we will predict convergence possibility of the similar research areas and Korea Intelligent Information Systems Society in overall ecosystem perspectives.

• Journal of The Korean Association For Science Education
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• v.44 no.3
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• pp.231-248
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• 2024

This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.1
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• pp.35-45
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• 2020

This study focused on the park as a space to support the behavior of urban citizens in modern society. Modern city parks are not spaces that play a specific role but are used by many people, so their function and meaning may change depending on the user's behavior. In addition, current online data may determine the selection of parks to visit or the usage of parks. Therefore, this study analyzed the change of behavior in Yeouido Park, Yeouido Hangang Park, and Yangjae Citizen's Forest from 2000 to 2018 by utilizing a time series analysis. The analysis method used Big Data techniques such as text mining and social network analysis. The summary of the study is as follows. The usage behavior of Yeouido Park has changed over time to "Ride" (Dynamic Behavior) for the first period (I), "Take" (Information Communication Service Behavior) for the second period (II), "See" (Communicative Behavior) for the third period (III), and "Eat" (Energy Source Behavior) for the fourth period (IV). In the case of Yangjae Citizens' Forest, the usage behavior has changed over time to "Walk" (Dynamic Behavior) for the first, second, and third periods (I), (II), (III) and "Play" (Dynamic Behavior) for the fourth period (IV). Looking at the factors affecting behavior, Yeouido Park was had various factors related to sports, leisure, culture, art, and spare time compared to Yangjae Citizens' Forest. The differences in Yangjae Citizens' Forest that affected its main usage behavior were various elements of natural resources. Second, the behavior of the target areas was found to be focused on certain main behaviors over time and played a role in selecting or limiting future behaviors. These results indicate that the space and facilities of the target areas had not been utilized evenly, as various behaviors have not occurred, however, a certain main behavior has appeared in the target areas. This study has great significance in that it analyzes the usage of urban parks using Big Data techniques, and determined that urban parks are transformed into play spaces where consumption progressed beyond the role of rest and walking. The behavior occurring in modern urban parks is changing in quantity and content. Therefore, through various types of discussions based on the results of the behavior collected through Big Data, we can better understand how citizens are using city parks. This study found that the behavior associated with static behavior in both parks had a great impact on other behaviors.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.843-856
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• 2023

The global surge in maritime traffic has resulted in an increased number of ship collisions, leading to significant economic, environmental, physical, and human damage. The causes of these maritime accidents are multifaceted, often arising from a combination of crew judgment errors, negligence, complexity of navigation routes, weather conditions, and technical deficiencies in the vessels. Given the intricate nuances and contextual information inherent in each incident, a methodology capable of deeply understanding the semantics and context of sentences is imperative. Accordingly, this study utilized the SentenceBERT model to analyze maritime safety tribunal decisions over the last 20 years in the Busan Sea area, which encapsulated data on ship collision incidents. The analysis revealed important keywords potentially responsible for these incidents. Cluster analysis based on the frequency of specific keyword appearances was conducted and visualized. This information can serve as foundational data for the preemptive identification of accident causes and the development of strategies for collision prevention and response.