• Title/Summary/Keyword: News Program

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Curriculum Analysis of Gerontological Nurse Practitioner Programs (노인전문간호사 교과과정 분석)

  • Lee, Hae Jung;Kim, Yeong Kyeong
    • Korean Journal of Adult Nursing
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    • v.19 no.4
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    • pp.656-669
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    • 2007
  • Purpose: The purposes of this article were to analyze curricula of gerontological nurse practitioner(GNP) programs in the United States, to compare the curricula with Korean GNP programs, and to provide suggestions for better GNP programs in Korea. Methods: Top GNP programs in the United States were identified from the US NEWS and 12 universities were included in the analyses. Class distribution, credit hours, and clinical hours were analyzed and suggestions for Korean GNP programs were made. Results: Average credit hours for class lectures in the US GNP programs were 47 and emphases on physiology, pharmacology, physical assessment, and disease management were identified. Most US GNP programs(75%) provided health concerns for both middle aged and older adults. Not all US GNP programs included 'theory' or 'the introduction to GNP' classes, while these are required classes in the Korean GNP program. The mean clinical hours in the US GNP Programs were 537 which are much higher than those in the Korean GNP program. Conclusion: Based on the analyses, we can conclude that Korean GNP programs are lacking in many ways. Further evaluation and curricula modifications are required to settle down the program better and to have the graduates prepared more as internationally competent nurse practitioners.

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Understanding the Food Hygiene of Cruise through the Big Data Analytics using the Web Crawling and Text Mining

  • Shuting, Tao;Kang, Byongnam;Kim, Hak-Seon
    • Culinary science and hospitality research
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    • v.24 no.2
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    • pp.34-43
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    • 2018
  • The objective of this study was to acquire a general and text-based awareness and recognition of cruise food hygiene through big data analytics. For the purpose, this study collected data with conducting the keyword "food hygiene, cruise" on the web pages and news on Google, during October 1st, 2015 to October 1st, 2017 (two years). The data collection was processed by SCTM which is a data collecting and processing program and eventually, 899 kb, approximately 20,000 words were collected. For the data analysis, UCINET 6.0 packaged with visualization tool-Netdraw was utilized. As a result of the data analysis, the words such as jobs, news, showed the high frequency while the results of centrality (Freeman's degree centrality and Eigenvector centrality) and proximity indicated the distinct rank with the frequency. Meanwhile, as for the result of CONCOR analysis, 4 segmentations were created as "food hygiene group", "person group", "location related group" and "brand group". The diagnosis of this study for the food hygiene in cruise industry through big data is expected to provide instrumental implications both for academia research and empirical application.

A Study on the Analysis of Museum Gamification Keywords Using Social Media Big Data

  • Jeon, Se-won;Choi, YounHee;Moon, Seok-Jae;Yoo, Kyung-Mi;Ryu, Gi-Hwan
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.4
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    • pp.66-71
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    • 2021
  • The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

Analysis of Media Trends and Social Perceptions on Nursing Law Legislation (간호법 제정에 대한 언론 동향 및 사회적 인식 분석)

  • Lee, Seung-Hee;Joo, Min-Ho
    • Journal of Korean Academy of Nursing
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    • v.53 no.4
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    • pp.439-452
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    • 2023
  • Purpose: This study aimed to derive considerations for the enactment of nursing law by analyzing the trends and social perceptions of nursing law mentioned in major daily newspapers, cafes, and blogs. Methods: Main texts and comments that included nursing law as a keyword were collected from major daily news and online postings from January 2021 to August 2022. The data collected through web crawling were analyzed using a TousFlux program used for big data analysis. Results: During the period of study, the awareness level around nursing law enactment increased. In particular, public concern over nursing law enactment intensified due to the two political parties' policy pledges related to nursing law in January 2022 and the failure to introduce the nursing law to the national assembly judiciary committee in May 2022. Except in December 2021, public perception of nursing law enactment was generally favorable, with public opinion tilting more in favor of than against enactment. Conclusion: Public opinion should be considered when drafting and implementing the nursing law to make it easier for the people to understand what the law constitutes. In addition, it is necessary to pay attention to and continuously promote the relationship between medical care and nursing in the nursing law system of developed nations. Lastly, nursing law enactment can enhance nurses' retention intention and provide a sense of efficacy to medical services.

Big Data Analytics Applied to the Construction Site Accident Factor Analysis

  • KIM, Joon-soo;Lee, Ji-su;KIM, Byung-soo
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.678-679
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    • 2015
  • Recently, safety accidents in construction sites are increasing. Accordingly, in this study, development of 'Big-Data Analysis Modeling' can collect articles from last 10 years which came from the Internet News and draw the cause of accidents that happening per season. In order to apply this study, Web Crawling Modeling that can collect 98% of desired information from the internet by using 'Xml', 'tm', "Rcurl' from the library of R, a statistical analysis program has been developed, and Datamining Model, which can draw useful information by using 'Principal Component Analysis' on the result of Work Frequency of 'Textmining.' Through Web Crawling Modeling, 7,384 out of 7,534 Internet News articles that have been posted from the past 10 years regarding "safety Accidents in construction sites", and recognized the characteristics of safety accidents that happening per season. The result showed that accidents caused by abnormal temperature and localized heavy rain, occurred frequently in spring and winter, and accidents caused by violation of safety regulations and breakdown of structures occurred frequently in spring and fall. Plus, the fact that accidents happening from collision of heavy equipment happens constantly every season was acknowledgeable. The result, which has been obtained from "Big-Data Analysis Modeling" corresponds with prior studies. Thus, the study is reliable and able to be applied to not only construction sites but also in the overall industry.

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Comparative Analysis of News Big Data related to SARS-CoV, MERS-CoV, and SARS-CoV-2 (COVID-19)

  • Woo, Jae-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.8
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    • pp.91-101
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    • 2021
  • This paper intends to draw implications for preparing for Post-Corona in the health field and policy fields as the global pandemic is experienced due to COVID-19. The purpose of this study is to analyze the news and trends of media companies through temporal analysis of the three infectious diseases, SARS-CoV, MERS-CoV, and SARS-CoV-2 (COVID-19), in which the domestic infectious disease preventive system was active throughout the first year of the outbreak. To this end, by using the news analysis program of the Korea Press Foundation 'Big Kinds', the number of news articles per year was digitized based on the period when each infectious disease had an impact on Korea, and major trends were implemented and analyzed in a word cloud. As a result of the analysis, the number of articles related to infectious diseases peaked when the World Health Organization (WHO) declared a warning and (suspicious) confirmed cases occurred. According to keyword and word cloud analysis, 'infectious disease outbreak and major epidemic areas', 'prevention authorities', and 'disease information and confirmed patient information' were found to be the main common features, and differences were derived from the three infectious diseases. In addition, the current status of the infodemic was identified by performing word cloud analysis on information in uncertainty. The results of this study are significant in that they were able to derive the roles of the health authorities and the media that should be preceded in the event of a new disease epidemic through previously experienced infectious diseases, and areas to be rearranged.

A Study on Securing Competitiveness of Contents in Local Broadcasting (지역방송 콘텐츠의 제작경쟁력 확보방안 연구)

  • Joo, Chungmin;Han, Jinmann
    • The Journal of the Korea Contents Association
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    • v.16 no.10
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    • pp.627-635
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    • 2016
  • The study analyzed what programs local broadcasting stations should produce to secure competitiveness in contents. As a result, in order to make more local people watch news programs, providing accurate local and general news and information and a forum for discussion on major issues is required. Moreover, it was revealed that providing a forum for discussion on local issues and representing the voice of local people based on accuracy, fairness and reliability is important to improve satisfaction with news. For increasing general program ratings of local broadcasts, it is required to provide interesting programs and encourage local people to participate in the programs. Additionally, in order to raise satisfaction with general programs, it is necessary to offer interesting and high quality programs, deal with local issues and information and provide local residents with a platform for participation.

A Topic Analysis of SW Education Textdata Using R (R을 활용한 SW교육 텍스트데이터 토픽분석)

  • Park, Sunju
    • Journal of The Korean Association of Information Education
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    • v.19 no.4
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    • pp.517-524
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    • 2015
  • In this paper, to find out the direction of interest related to the SW education, SW education news data were gathered and its contents were analyzed. The topic analysis of SW education news was performed by collecting the data of July 23, 2013 to October 19, 2015. By analyzing the relationship among the most mentioned top 20 words with the web crawling using R, the result indicated that the 20 words are the closely relevant data as the thickness of the node size of the 20 words was balancing each other in the co-occurrence matrix graph focusing on the 'SW education' word. Moreover, our analysis revealed that the data were mainly composed of the topics about SW talent, SW support Program, SW educational mandate, SW camp, SW industry and the job creation. This could be used for big data analysis to find out the thoughts and interests of such people in the SW education.

Features of the Rural Revitalization Projects in Jang-su County Using LDA Topic Analysis of News Data - Focused on Keyword of Tourism and Livelihood - (뉴스데이터의 LDA 토픽 분석을 통한 장수군 농촌지역 활성화 사업의 특징 - 관광·생활 키워드를 중심으로 -)

  • Kim, Young-Jin;Son, Yong-hoon
    • Journal of Korean Society of Rural Planning
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    • v.24 no.4
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    • pp.69-80
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    • 2018
  • In this study, we typified the project for revitalizing the rural area through text analysis using news data, and analyzed the main direction and characteristics of the project. In order to examine the factors emphasized among the issues related to the revitalization of rural areas, we used news data related to 'tourism' and 'livelihood', which are the main keyword of the project to promote rural areas. In the analysis, text mining techniques were used. Topic modeling was conducted on LDA techniques for major projects in 'tourism' and 'livelihood' keyword. Based on this, this study typified the projects that are carried out for the activation of rural areas by topic. As a result of the analysis, it was fount that the topics included in the project were distributed in 11 sub-types(Tourism Promotion, Regional Specialization, Local Festival, Development of Regional Scale, Urban and Rural Exchange, Agricultural Support, Community Forest Management, Improve the Settlement Environment, General Welfare Service, Low Class Support, Others). The characteristics of the rural revitalization projects were examined, and it was confirmed that domestic projects were carried out by tourism-oriented projects. To summarize, the government is making projects to revitalize rural areas through related ministries. Within the structure where the project is spreading to the region, a lot of projects are being carried out. It is understood that the tourism and welfare oriented projects are being carried out in the revitalization project of the domestic rural area. Therefore, in order to achieve the goal of rural revitalization, it is believed that it will be effective to carry out a balanced project to improve the settlement environment of the residents.

Consumers Perceptions on Monosodium L-glutamate in Social Media (소셜미디어 분석을 통한 소비자들의 L-글루타민산나트륨에 대한 인식 조사)

  • Lee, Sooyeon;Lee, Wonsung;Moon, Il-Chul;Kwon, Hoonjeong
    • Journal of Food Hygiene and Safety
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    • v.31 no.3
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    • pp.153-166
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    • 2016
  • The purpose of this study was to investigate consumers' perceptions on monosodium L-glutamate (MSG) in social media. Data were collected from Naver blogs and Naver web communities (Korean representative portal web-site), and media reports including comment sections on a Yonhap news website (Korean largest news agency). The results from Naver blogs and Naver web communities showed that it was primarily mentioned MSG-use restaurant reviews, 'MSG-no added' products, its safety, and methods of reducing MSG in food. When TV shows on current affairs, newspaper, or TV news reported uses and side effects of MSG, search volume for MSG has increased in both PC and mobile search engines. Search volume has increased especially when TV shows on current affairs reported it. There are more periods with increased search volume for Mobile than PC. Also, it was mainly commented about safety of MSG, criticism of low-quality foods, abuse of MSG, and distrust of government below the news on the Yonhap news site. The label of MSG-no added products in market emphasized "MSG-free" even though it is allocated as an acceptable daily intake (ADI) not-specified by the Joint FAO/WHO Expert Committee on Food Additives (JECFA). When consumers search for MSG (monosodium L-glutamate) or purchase food on market, they might perceive that 'MSG-no added' products are better. Competent authorities, offices of education and local government provide guidelines based on no added MSG principle and these policies might affect consumers' perceptions. TV program or news program could be a powerful and effective consumer communication channel about MSG through Mobile rather than PC. Therefore media including TV should report item on monosodium L-glutamate with responsibility and information based on scientific background for consumers to get reliable information.