• Title/Summary/Keyword: keyword frequency analysis

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Study on the Viewers' Perception of Investigative Journalism Before and After Pandemic Using Big Data (빅데이터를 활용한 팬데믹 전후 탐사보도프로그램에 대한 시청자 인식연구)

  • Kyunghee Kim;Soonchul Kwon;Seunghyun Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.311-320
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    • 2023
  • This paper analyzes viewers' perception of investigative journalism before and after COVID-19, and examines the direction of investigative journalism using big data. Based on the previous research set as a social science model, the relationship between words related to big data TV current affairs programs and investigative journalism in this paper was investigated before and after the appearance of COVID-19. We visualized changes in viewers' perception of investigative journalism by analyzing text data obtained through the use of Textom, with TV current affairs programs and investigative journalism as keywords. Data was collected from 2017 to June 2022 and refined for analysis. We visualized connectivity centrality using Ucinet 6.0 and Netdraw, and clustered the number of keywords and their frequency using Concor analysis. Our study found a clear change in viewer perception before and after the pandemic. As an implication of this thesis, big data analysis was conducted with the investigative journalism as the main keyword, and the direction of the investigative journalism was presented based on the analysis. Furthermore, based on previous research, we suggest effective approaches for investigative journalism after the pandemic to better engage viewers.

A Study on the Trends in the Studies on Marine Spatial Planning: Focusing on Topic Modeling (해양공간계획 연구동향 분석 연구: 토픽 모델링을 중심으로)

  • Hwang, Kyu Won;Jang, Ah Reum;Lee, Moon Suk
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.7
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    • pp.954-966
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    • 2021
  • With regards to the marine spatial plannings of the world, the spaces are being managed through the integration of various uses and the establishment of systems and laws in the perspective of the utilization of spaces. In the perspective of policy establishment, the policy readiness level is applied to analyze the trends in the studies on South Korea's marine spatial plans. The scope of the study included analyzing marine spatial plan as a keyword in articles published over the period from 2010 to 2020. The methods of analysis included the analyses of the frequency of word appearance, word clouds, and appearance intensity, which were used to identify key issues. Five keywords that were related to the topics were identified, and were again used to identify the key themes. The core themes were changing in all phases, such as the principles development phase, institutionalization phase, policy verification phase. For future benefit, this requires more research in South Korean public organizations and universities.

A Semantic Analysis on the Research Trend of International Arts Management (언어네트워크분석을 활용한 해외 예술경영 연구동향 연구)

  • Shim, Dahee;Park, Yang Woo
    • Korean Association of Arts Management
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    • no.49
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    • pp.5-35
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    • 2019
  • The main purpose of this study was to use semantic network analysis to examine the international trend of arts management and other studies pertinent to this field. The subject was based on 357 keywords listed on the abstract of 185 research papers in the International Journal of Arts Management. To examine the most current trends of arts management based studies the time frame was restricted from 2008 to 2017. To briefly summarize the result, first, 'museum' was the most frequently appeared keyword. This was followed by 'performing arts' and 'arts' with more than 20 appearances. 'Motion picture industry' and 'theater' were the next frequently appeared keywords. 'Customer behavior' and 'market strategy', keywords related to management, were also included in the high ranked group along with art related keywords. Second, yearly research trend shows that arts management has been regularly studied for past ten years with average of 19 research papers with about 53 keywords. Keywords such as 'museum' and 'performing arts' has been regularly studied for past ten years. 'Culture', 'theater' and 'motion pictures industry' does not regularly appear in the result of yearly research trend but nevertheless they have sparsely made an appearance along the past decade. 'Art gallery' has not been cited till 2011 but from 2012 it was regularly and continuously made an appearance in the yearly research trend. Overall, the yearly trend result shows that the trend of international arts management studies within IJAM, was at first centered on fine arts but as the time passed there has been diversified keywords related to management. Third, 'performing art' and 'art' has the highest link frequency(34). Fourth, density result was 0.039 which shows that the keyword density is not very high. Fifth, 'art', 'performing art', 'museum', 'theater' and 'brand' were positioned in the middle when looking at the visualized version of centrality result. This means that these five keywords has the highest centrality among other keywords.

Complaint-based Data Demands for Advancement of Environmental Impact Assessment (환경영향평가 고도화를 위한 평가항목별 민원기반 데이터 수요 도출 연구)

  • Choi, Yu-Young;Cho, Hyo-Jin;Hwang, Jin-Hoo;Kim, Yoon-Ji;Lim, No-Ol;Lee, Ji-Yeon;Lee, Jun-Hee;Sung, Min-Jun;Jeon, Seong-Woo;Sung, Hyun-Chan
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.24 no.6
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    • pp.49-65
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    • 2021
  • Although the Environmental Impact Assessment (EIA) is continuously being advanced, the number of environmental disputes regarding it is still on the rise. In order to supplement this, it is necessary to analyze the accumulated complaint cases. In this study, through the analysis of complaint cases, it is possible to identify matters that need to be improved in the existing EIA stages as well as various damages and conflicts that were not previously considered or predicted. In the process, we dervied 'complaint-based data demands' that should be additionally examined to improve the EIA. To this end, a total of 348 news articles were collected by searching with combinations of 'environmental impact assessment' and a keyword for each of the six assessment groups. As a result of analysis of collected data, a total of 54 complaint-based data demands were suggested. Among those were 15 items including 'impact of changes in seawater flow on water quality' in the category of water environment; 13 items including 'area of green buffer zone' in atmospheric environment; 10 items including 'impact of soundproof wall on wind corridor' in living environment; 8 items including 'expected number of users' in socioeconomic environment, 4 items including 'feasibility assessment of development site in terms of environmental and ecological aspects' in natural ecological environment; and 4 items including 'prediction of sediment runoff and damaged areas according to the increase in intensity and frequency of torrential rain' in land environment. In future research, more systematic complaint collection and analysis as well as specific provision methods regarding stages, subjects, and forms of use should be sought to apply the derived data demands in the actual EIA process. It is expected that this study can serve to advance the prediction and assessment of EIA in the future and to minimize environmental impact as well as social conflict in advance.

Research Trends in English-Language Journals of Korean Studies Published in Korea (국내에서 간행된 한국학 분야 영문학술지의 연구 동향 분석)

  • Min Jung, Kim;Hye-Eun, Lee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.34 no.1
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    • pp.145-166
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    • 2023
  • This study aims to analyze the research trends of English-language journals in Korean studies published in Korea. Data were collected from four English journals in Korean studies indexed in A&HCI and SCOPUS. A total of 1,840 were selected, including 768 articles of the Korea Journal, 466 articles of The Review of Korean Studies, 285 articles of the Seoul Journal of Korean Studies, and 321 articles of the Acta Koreana, in connection with content analysis, author analysis, author keyword frequency analysis, and topic modeling. In results, the domain research of Korean studies is Humanities, followed by Social Science, and Arts and Kinesiology. These three sectors have grown significantly in publishing numbers since 2000. The subject period of the study is in the order of the modern period, late Joseon, and Japanese colonial period. Authors from domestic affiliations made up 73.34% of the total, but the proportion of authors belonging to foreign institutions continued to increase. As for author keywords, 'Korea'(41), 'Buddhism'(20), 'Koreanwar'(18), and 'Joseon'(18) were derived as top keywords. In topic modeling, six topics were identified; 'Korean culture, cultural transmission,' 'Korean modern political history,' 'Korean social democratization process,' 'Japanese colonial period,' 'Korean religious philosophy,' and 'Korean ancient history.' Through this study, it was possible to identify the interests in and research areas of the recent international academic community of Korean studies.

Maritime Safety Tribunal Ruling Analysis using SentenceBERT (SentenceBERT 모델을 활용한 해양안전심판 재결서 분석 방법에 대한 연구)

  • Bori Yoon;SeKil Park;Hyerim Bae;Sunghyun Sim
    • 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.

Analysis of Research Trends Related to drug Repositioning Based on Machine Learning (머신러닝 기반의 신약 재창출 관련 연구 동향 분석)

  • So Yeon Yoo;Gyoo Gun Lim
    • Information Systems Review
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    • v.24 no.1
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    • pp.21-37
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    • 2022
  • Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.

A Study on Changes in Interest and Awareness of Adolescents' Dietary Habits Before and After COVID-19 (코로나19 전후 청소년의 식생활에 대한 관심과 인식 변화 연구)

  • Oh, Sang-Mi;Jung, Lan-Hee;Jeon, Eun-Raye
    • Journal of Korean Home Economics Education Association
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    • v.36 no.2
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    • pp.1-13
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    • 2024
  • This study used TEXTOM for a total of 4 years, 2 years before and after, as of January 19, 2020, when the domestic confirmed cases of COVID-19 were officially announced, targeting Naver, Daum, Google, YouTube, and Twitter. By analyzing changes in adolescents' interest and awareness of their dietary habits, we aimed to create an opportunity to develop a dietary education program to provide proper dietary education. The results obtained through this study are as follows. First, the keywords with the highest co-occurrence before COVID-19 were 'nutrition' and 'counseling', and the next keywords were 'nutrition' and 'education'. After COVID-19, the order was 'nutrition', 'education', 'food' and 'safety'. Second, the results of co-occurrence frequency network analysis showed that there was high interest in nutrition and counseling regardless of COVID-19, and that interest in safety and health increased further after COVID-19. Third, through cluster formation through CONCOR analysis, before COVID-19, it was categorized into 'diet and physical activity', 'skin and disease', 'health and food', and 'nutrition and intake', and after COVID-19, it was categorized into 'nutrition, intake and COVID-19', 'diet and physical activity', 'skin and disease', and 'circadian rhythm imbalance and disease'. Fourth, as a result of the diet-related keyword cluster analysis network, before COVID-19, keywords in the 'eating and physical activity' group were strongly connected to keywords in the 'health and food' and 'nutrition and intake' groups, and after COVID-19, 'diet' Keywords in the 'and physical activity' group were strongly connected to keywords in the 'nutrition, intake, and COVID-19' group.

A Comparative Analysis on Keywords of International and Korean Journals in Library and Information Science (국내외 문헌정보학 저널의 키워드 비교 분석)

  • Kim, Eungi
    • Journal of Korean Library and Information Science Society
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    • v.48 no.1
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    • pp.207-225
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    • 2017
  • The aim of this study was to discover various Library and Information Science (LIS) research areas by examining similarities and differences between LIS journals in terms of keyword characteristics. To conduct this study, for the years from 2004 to 2016, the keywords of 6 international journals were downloaded from Scopus database (http://www.scopus.com), and the keywords of 4 Korean journals were downloaded from the RISS database (http://www.riss.co.kr). The characteristics of keywords were investigated by examining frequently used keywords and frequently used distinctive keywords pertaining to international and Korean journals. The distinctive keywords are referred to as the keywords that appear in one domain but not in another. The result of this study indicated the following: a) a frequency analysis of the keywords showed major research themes and unique traits concerning Korea. b) In general, the keywords used in Korean journals frequently reflected the library as a major subject area of research, while keywords used in international journals reflected bibliometrics and information retrieval as major subject areas of research. c) The overarching themes of each created dataset were clearly noticeable in frequently used distinctive keywords. d) Some keywords were bound by a nation or by a region due to their scope of usage. The important implication of this study is that both most frequently used keywords and most frequently used distinctive keywords seemed to adequately represent the LIS subject areas.

A Comparative Analysis of Disaster-Related Curriculum between Emergency Department and Nursing Department

  • Jung, Ji-Yeon
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.10
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    • pp.183-188
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    • 2019
  • This study is a descriptive research to compare and analyze the current status of disaster-related curriculum between emergency department and nursing department Research and analysis targets were 41 universities which include the emergency department in South Korean by using the universities' internet homepage, finally 30 universities were researched by removing the universities which doesn't upload the curriculum on their homepage, have emergency department or have nursing department. The research data were collected and analyzed by using the universities' internet homepage. The Keyword is 'Disaster', 'Catastrophe', and 'Emergency' to search the name of the subjects. The curriculum calculated as a percentage of frequency by using the status of disaster-related subjects opening, classification of major education, grade, credit, number of class, practical hours, and the total number of subjects. According to the study, 29 universities (96.7%) of emergency department and 19 universities (63.3%) of nursing department has the disaster-related subjects in their curriculum. The current status of the class opening is emergency department at second grade and nursing department as fourth grade. As a subject of major, two credits are the common class credits. Based on the results of the study, knowledge and skills and training courses are necessary to develop the ability to cope with disasters in the disaster field. The curriculum that matches the role of health care resources will be required.