• Title/Summary/Keyword: Keyword Trends

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Trend Analysis of Research Articles Published in the Korean Journal of Women Health Nursing from 2013 to 2017 (최근 4년간 여성건강간호학회지에 게재된 여성건강 관련 연구의 동향(2013~2017년))

  • Lee, Young Jin;Kim, Seo Yun;Kang, Saem Yi;Kang, Yoo Jeong;Jin, Lan;Jung, Hee Yoen;Kim, Hae Won
    • Women's Health Nursing
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    • v.24 no.1
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    • pp.90-103
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    • 2018
  • Purpose: To analyze articles published in the Korean Journal of Women Health Nursing from 2013 to 2017 to determine the latest research trends and understand how 2013 Korea Women's Health Statistics were reflected in journal articles. Methods: A total of 130 studies were analyzed. Research design, types of research, research framework, research subjects, characteristics of quantitative research, characteristics of qualitative research, and keywords were analyzed using a structured analysis format. Results: Quantitative and qualitative research accounted for 83.8% and 13% of these 130 studies analyzed, respectively. Non-experimental and experimental research accounted for 70.7% and 13.1% of these studies, respectively. The most frequent study subjects were childbearing women (62.8%), including college students, mothers, and adults. A total of 69.1% of non-experimental research and 88.2% of experimental research used convenience sampling. Questionnaires were most frequently used for data collection. The most frequent keyword domain involved health-related concepts (41%) among nine domains and the most frequently used keyword was "women." Conclusion: This study suggest that further experimental research should be conducted in the future. Also, adolescent and the elderly women should be focused on as subjects in future studies based on results of 2013 Korean Women's Health Statistics.

Network Analysis of the Intellectual Structure of Addiction Research in Social Sciences: Based on the KCI Articles Published in 2019 (사회과학 중독연구 분야의 지적구조에 관한 네트워크 분석 : 2019년도 KCI 등재 논문을 기반으로)

  • Lee, Serim;Chun, JongSerl
    • The Journal of the Korea Contents Association
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    • v.21 no.10
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    • pp.21-37
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    • 2021
  • This study investigated the intellectual structure of the latest trends in Korean addiction research in the social sciences. A network analysis of keywords with co-word occurrence was performed on 172 papers from the KCI database based on the data from the year of 2019, and a total of 432 keywords were extracted. The network analysis was performed using several programs: Bibexcel, COOC, WNET, and NodeXL. As a result of the study, keywords related to addiction type, study subjects, research methods, and research variables were found, and a total of 20 clusters were identified. Furthermore, to identify and measure weighted networks, the relationships between each keyword were explored and discussed in detail through a network analysis of global centralities, local centralities, and betweenness centralities. The study indicated that the latest issues were focused on smartphone addiction and provided implications for the future research and practice that fields and topics of relationship addiction, food addiction, and work addiction should be more considered. Further, the study discussed the relationship between drug addiction-crime, alcohol addiction-family, and gambling addiction-motivation and the necessity of qualitative study.

A Study on Research Trend in Field of Busan Port by Social Network Analysis (SNA를 활용한 부산항 연구동향 분석에 관한 연구)

  • Kim, Mi-Jin;Park, Sung-Hoon;Kim, Yu-Na;Lee, Hae-Chan;Yeo, Gi-Tae
    • Journal of Digital Convergence
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    • v.19 no.2
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    • pp.117-133
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    • 2021
  • This study aimed to identify its research trends using social network analysis(SNA). The results of the analysis showed that, for degree centrality, Busan Port(0.223) was the keyword that had the highest centrality, followed by DEA(0.060), AHP(0.056), and container terminal and port competitiveness(0.049). Busan Port(0.245) also had the highest betweenness centrality, followed by DEA(0.048), container terminal(0.044), AHP(0.039), and Busan New Port(0.032). The trend analysis inferred that efficiency analysis(DEA), strategy selection, and competition analysis(AHP) were the keywords with a high centrality for Busan Port to gain a competitive edge with global ports. However, research on the Fourth Industrial Revolution, which is emerging as a key issue, was insufficient. In the future, research using social data, such as mass media and social networks, is necessary.

How Does the Media Deal with Artificial Intelligence?: Analyzing Articles in Korea and the US through Big Data Analysis (언론은 인공지능(AI)을 어떻게 다루는가?: 뉴스 빅데이터를 통한 한국과 미국의 보도 경향 분석)

  • Park, Jong Hwa;Kim, Min Sung;Kim, Jung Hwan
    • The Journal of Information Systems
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    • v.31 no.1
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    • pp.175-195
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    • 2022
  • Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

Expanding Research Topics in Foodservice and Restaurant Management: Rethinking Two Decades Bibliometrics in the Journal of the Korean Society of Food Culture (급식·외식 연구주제의 확장: 한국식생활문화학회지의 20년간의 서지학적 재고)

  • Han, Kyungsoo;Lee, Haeyoung;Shin, Sunhwa;Chai, Insuk
    • Journal of the Korean Society of Food Culture
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    • v.37 no.3
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    • pp.179-195
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    • 2022
  • For any research study, in order to achieve the researcher's intended purpose, the depth of research is added, and the area of the subject is expanded by clearly defining the scope and objective. The study was undertaken to analyze the bibliographic data of 254 papers in the field of foodservice and restaurant published in the Journal of the Korean Dietary Culture from 2002 to 2021. The study was divided into two periods: 2002 to 2011, and 2012 to 2021. Research topics were derived and research trends according to temporal changes were confirmed through analysis of keyword networks by period. In addition, analyzing the keyword network of simultaneous appearance of "foodservice" and "restaurant", the research topics were compared and analyzed in relation to which keywords were expanded by period. Our analysis revealed that the research topics were mostly studied for satisfaction and nutrition. Additionally, they were classified into procurement, Korean food before employee menu, marketing, restaurant industry, and quality. In the period from 2002 to 2011, it was confirmed that studies encompassed a wide range of research topics, focusing on foodservice and restaurant; in the second period from 2012 to 2021, the research topics were more classified and subdivided.

Research Trend Analysis of Research Published in the Journal of Dental Hygiene Science from 2011 to 2020

  • Lee, Sun-Mi;Seong, Mi-Gyung;Moon, Hee-Jung;Son, Jung-Hui
    • Journal of dental hygiene science
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    • v.22 no.3
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    • pp.131-138
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    • 2022
  • Background: The purpose of this study was to analyze research trends in articles published in the Journal of Dental Hygiene Science over the past decade. Methods: From 2011 to 2020, 653 studies were reviewed using a keyword analysis. Contents such as academic classification, research type, research method, research topic, data collection method, data analysis method, and financial support were analyzed. Results: Analysis by school type showed 34.2% of clinical dental hygiene studies, 23.3% of educational dental hygiene studies, 22.8% of basic dental hygiene studies, 10.0% of other field studies, and 9.8% of social dental hygiene studies. By type of study, quantitative studies were the most common at 69.5%. Regarding data collection methods, 45.8% of the studies that used surveys were the most common. The subjects of the study were 20.1% experimental studies, 15.6% general adults, and 15.0% dental hygienists. Regarding the data analysis method, 49.3% of the studies that conducted frequency analysis were the most common. The total number of keywords was 2,390, with 107 (4.48%) being 'dental hygienists.' Next, oral health was the most common with 67 (2.80%) articles, followed by 31 for the elderly (1.30%), 25 for dental hygiene students (1.05%), and 24 for stress (1.00%). Conclusion: For academic development of dental hygiene, it is necessary to explore the diversity of academic topics based on the results of this study. It is necessary to find a way to spread the research results so that the published research can be used for the academic development of dental hygiene.

Analysis of national R&D projects related to herbal medicine (2002-2022) (한약 관련 국가연구개발사업 분석 및 고찰 (2002-2022))

  • Anna Kim;Seungho Lee;Young-Sik Kim
    • Herbal Formula Science
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    • v.31 no.2
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    • pp.81-98
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    • 2023
  • Objectives : This study aimed to analyze the trends in research and development projects related to herbal medicine and natural products in the field of traditional Korean medicine (TKM) over the past 20 years. Methods : Research projects were identified using "Korean medicine" as the subject heading in the National Science and Technology Information Service. The included projects investigated Korean medicine, natural products, or were related to the TKM industry. Data pre-processing and network analysis were performed using Python and Networkx package, and the network was visualized using the ForceAtlas2 visualization algorithm. Results : 1. Over the study period, 4,020 projects were conducted with a research budget of KRW 835.2 billion. Seven institutions performed over 100 projects each, accounting for 2.4% of all participating institutions, and the top 10 institutions accounted for 58.9% of total projects. 2. Obesity was the most frequently mentioned disease-related keyword. Chronic or age-related diseases such as diabetes, osteoporosis, dementia, parkinson's disease, cancer, inflammation, and asthma were also frequent research topics. Clinical research, safety, and standardization were also frequently mentioned. 3. Centrality analysis found that obesity was the only disease-related keyword identified, alongside TKM-related keywords. Standardization, safety, and clinical trials were identified as central keywords. Conclusions : The study found that research projects in TKM have focused on standardizing and ensuring the safety of herbal medicine, as well as on chronic and age-related diseases. Clinical studies aimed at verifying the effectiveness of herbal medicine were also frequent. These findings can guide future research and development in herbal medicine.

Text Network Analysis and Topic Modeling of News Articles on Lonely Death (고독사에 관한 언론보도기사의 텍스트네트워크 분석 및 토픽모델링)

  • Kim, Chunmi;Choi, Seungbeom;Kim, Eun Man
    • Journal of Korean Academy of Rural Health Nursing
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    • v.18 no.2
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    • pp.113-124
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    • 2023
  • Purpose: The number of households vulnerable to isolation increases rapidly as social ties decrease, raising concerns about the associated increase in lonely deaths. This study aimed to identify issues related to lonely deaths by analyzing South Korean news articles; and to provide evidence for their use in preventing and managing lonely deaths via community nursing. Methods: This exploratory study analyzed the structure and trends of meaning of lonely deaths by identifying the association between keywords in news articles and lonely deaths. In this study, we searched for all news articles on lonely deaths, covering the period from January 1, 2010, to May 31, 2023. Data preprocessing and purification were conducted, followed by top-keyword extraction, keyword network analysis and topic modeling. The retrieved articles were analyzed using R and Python software. Results: Four main topics were identified: "discovering and responding to lonely death cases", "lonely deaths ending in lonely funerals", "supportive policies to prevent lonely deaths among of older adults", and "local government activities to prevent lonely deaths and support vulnerable populations." Conclusion: Based on these findings, it can be concluded that lonely death is a complex social phenomenon that can be prevented if society shows concern and care. Education related to lonely deaths should be included in nursing curricula for concrete action plans and professional development.

Analysis of Research Trends of Explosion Accidents Using Co-Occurrence Keyword Analysis (동시출현 핵심단어 분석을 활용한 폭발사고 연구 동향 분석)

  • Youngwoo Lee;Minju Kim;Jeewon Lee;Wusung An;Sangki, Kwon
    • Explosives and Blasting
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    • v.42 no.2
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    • pp.12-28
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    • 2024
  • Explosion involving rapid energy diffusion are causing enormous human and economic damage. Due to the advancement of the industry, various and widespread explosion accidents are occurring worldwise, and to prevent such explosion accidents, accurate cause analysis should be the basis. Research analysis related to worldwise explosion accidents was carried out in a limited range for some accidents. By conducting bibliometric analysis of keywords on all the papers published in international journals, this study attempted to derive the overall research trend by period and the latest fields in which future researchers may be interested. As a result of the study of keywords, the number of papers was generally small and the number of overall key words was small from 2005 to 2014, but numerical simulation and artificial intelligence have been used for the analysis of explosion accident cases since 2015, and various studies such as lithium-ion battery and mixed gas, which are the latest research fields, are currently being actively conducted.

Comparative Exploration of Gyeongin Ara Waterway Recognition Before and After COVID-19 Outbreak Using Unstructured Big Data (비정형 빅데이터를 활용한 코로나19 발병 전후 경인 아라뱃길 인식 비교 탐색)

  • Han Jangheon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.20 no.1
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    • pp.17-29
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    • 2024
  • The Gyeongin Ara Waterway is a regional development project designed to transport cargo by sea and to utilize the surrounding waterfront area to enjoy tourism and leisure. It is being used as a space for demonstration projects for urban air transportation (UAM), which has recently been attracting attention, and various efforts are being made at the local level to strengthen cultural and tourism functions and revitalize local food. This study examined the perception and trends of tourism consumers on the Gyeongin Ara Waterway before and after the outbreak of COVID-19. The research method utilized semantic network analysis based on social network analysis. As a result of the study, first, before the outbreak of COVID-19, key words such as bicycle, Han River, riding, Gimpo, Seoul, hotel, cruise ship, Korea Water Resources Corporation, emotion, West Sea, weekend, and travel showed a high frequency of appearance. After the outbreak of COVID-19, keywords such as cafe, discovery, women, Gimpo, restaurant, bakery, observatory, La Mer, and cruise ship showed a high frequency of appearance. Second, the results of the degree centrality analysis showed that before the outbreak of COVID-19, there was increased interest in accommodations for tourism, such as Marina Bay and hotels. After the outbreak of COVID-19, interest in food such as specific bakeries and cafes such as La Mer was found to be high. Third, due to the CONCOR analysis, five keyword clusters were formed before the outbreak of COVID-19, and the number of keyword clusters increased to eight after the outbreak of COVID-19.