• Title/Summary/Keyword: News Article

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An Analysis of Changes in Social Issues Related to Patient Safety Using Topic Modeling and Word Co-occurrence Analysis (토픽 모델링과 동시출현 단어 분석을 활용한 환자안전 관련 사회적 이슈의 변화)

  • Kim, Nari;Lee, Nam-Ju
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.92-104
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    • 2021
  • This study aims to analyze online news articles to identify social issues related to patient safety and compare the changes in these issues before and after the implementation of the Patient Safety Act. This study performed text mining through the R program, wherein 7,600 online news articles were collected from January 1, 2010, to March 5, 2020, and examined using keyword analysis, topic modeling, and word co-occurrence network analysis. A total of 2,609 keywords were categorized into 8 topics: "medical practice", "medical personnel", "infection and facilities", "comprehensive nursing service", "medicine and medical supplies", "system development and establishment for improvement", "Patient Safety Act" and "healthcare accreditation". The study revealed that keywords such as "patient safety awareness", "infection control" and "healthcare accreditation" appeared before the implementation of the Patient Safety Act. Meanwhile, keywords such as "patient safety culture". and "administration and injection" appeared after the act's implementation with improved ranking of importance pertaining to nursing-related terminology. Interest in patient safety has increased in the medical community as well as among the public. In particular, nursing plays an important role in improving patient safety. Therefore, the recognition of patient safety as a core competency of nursing and the persistent education of the public are vital and inevitable.

Text Mining Analysis of News Articles Related to 'Space Hazard' ('우주 위험' 관련 뉴스 기사의 텍스트 마이닝 분석 연구)

  • Jo, Hoon;Sohn, Jungjoo
    • Journal of the Korean earth science society
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    • v.43 no.1
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    • pp.224-235
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    • 2022
  • This study aimed to confirm the status of media reports on space hazards using topic modeling analysis of media articles that are related to space hazards for the past 12 years. Therefore, Latent Dirichlet Allocation (LDA) analysis was performed by collecting over 1200 space hazards articles between 2010 and 2021 on solar storm, artificial space objects, and natural space objects from BIGKins news platform. The articles related to solar storm focused on three topics: the effect of solar explosion on satellites; effect of solar explosion on radio communication in Korea, centered on the Korean Space Weather Center; and relationship between aircrew and space radiation. The articles related to artificial space objects focused on three topics: the threat of space garbage to satellite and space stations and the transition of useful objects into space junk; the relationship between space garbage and humanity as shown in movies; and the effort of developed countries for tracking, monitoring, and disposing of space garbage. The articles related to natural space objects focused on two topics: International Space Agency's tracking and monitoring of near-Earth asteroids and the countermeasures of collisions, and the evolution and extinction of dinosaurs and mammals, with a focus on the collisions of asteroids or comets. Therefore, this study confirmed that domestic media play a role in conveying dangers of space hazards and arousing the attention of public using a total of eight themes in various fields such as society and culture, and derived education method and policy on space hazards.

A Study on the Perception and Experience of Daejeon Public Library Users Using Text Mining: Focusing on SNS and Online News Articles (텍스트마이닝을 활용한 대전시 공공도서관 이용자의 인식과 경험 연구 - SNS와 온라인 뉴스 기사를 중심으로 -)

  • Jiwon Choi;Seung-Jin Kwak
    • Journal of the Korean Society for Library and Information Science
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    • v.58 no.2
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    • pp.363-384
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    • 2024
  • This study was conducted to examine the user's experiences with the public library in Daejeon using big data analysis, focusing on the text mining technique. To know this, first, the overall evaluation and perception of users about the public library in Daejeon were explored by collecting data on social media. Second, through analysis using online news articles, the pending issues that are being discussed socially were identified. As a result of the analysis, the proportion of users with children was first high. Next, it was found that topics through LDA analysis appeared in four categories: 'cultural event/program', 'data use', 'physical environment and facilities', and 'library service'. Finally, it was confirmed that keywords for the additional construction of libraries and complex cultural spaces and the establishment of a library cooperation system appeared at the core in the news article data. Based on this, it was proposed to build a library in consideration of regional balance and to create a social parenting community network through business agreements with childcare and childcare institutions. This will contribute to identifying the policy and social trends of public libraries in Daejeon and implementing data-based public library operations that reflect local community demands.

Analyzing Different Contexts for Energy Terms through Text Mining of Online Science News Articles (온라인 과학 기사 텍스트 마이닝을 통해 분석한 에너지 용어 사용의 맥락)

  • Oh, Chi Yeong;Kang, Nam-Hwa
    • Journal of Science Education
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    • v.45 no.3
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    • pp.292-303
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    • 2021
  • This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

Trend of Fire Outbreaks in Ghana and Ways to Prevent These Incidents

  • Addai, Emmanuel K.;Tulashie, Samuel K.;Annan, Joe-Steve;Yeboah, Isaac
    • Safety and Health at Work
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    • v.7 no.4
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    • pp.284-292
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    • 2016
  • Background: In Ghana, fire incidents have become a regular occurrence, with thousands of lives and millions of dollars lost every year. Hardly a day passes without news of a fire outbreak in some part of Ghana, causing fear and panic among the people. This generates much discussion centering on rumors relating to politics, sabotage, misfortune, religious differences, etc. This article seeks to discuss the trend of fire incidents occurring in Ghana from 2000 to 2013 and the different ways to prevent these incidents. Methods: The pattern of fire incidence in Ghana as a whole as well as in each region is discussed. The study took into consideration the causes, mechanisms, as well as preventive measures against the fire menace. Data were obtained from the head office of Ghana's national fire service. Results: It was noticed that in general the rate of fire incidence increased each year. This increase was attributed to several factors: rate of population growth and industrialization, unstable electricity, urbanization, negligence, illegal electrical connection, etc. The cause of fire was categorized into domestic, industrial, vehicular, institutional, electrical, commercial, bush, and others. Among these causes, domestic fire accounted for 41% of the total number of fire incidents in the country. Conclusion: Finally, this study presents several recommendations to help prevent and mitigate fire incidents in Ghana.

Detecting Improper Sentences in a News Article Using Text Mining (텍스트 마이닝을 이용한 기사 내 부적합 문단 검출 시스템)

  • Kim, Kyu-Wan;Sin, Hyun-Ju;Kim, Seon-Jin;Lee, Hyun Ah
    • Annual Conference on Human and Language Technology
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    • 2017.10a
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    • pp.294-297
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    • 2017
  • SNS와 스마트기기의 발전으로 온라인을 통한 뉴스 배포가 용이해지면서 악의적으로 조작된 뉴스가 급속도로 생성되어 확산되고 있다. 뉴스 조작은 다양한 형태로 이루어지는데, 이 중에서 정상적인 기사 내에 광고나 낚시성 내용을 포함시켜 독자가 의도하지 않은 정보에 노출되게 하는 형태는 독자가 해당 내용을 진짜 뉴스로 받아들이기 쉽다. 본 논문에서는 뉴스 기사 내에 포함된 문단 중에서 부적합한 문단이 포함되었는지를 판정하기 위한 방법을 제안한다. 제안하는 방식에서는 자연어 처리에 유용한 Convolutional Neural Network(CNN)모델 중 Word2Vec과 tf-idf 알고리즘, 로지스틱 회귀를 함께 이용하여 뉴스 부적합 문단을 검출한다. 본 시스템에서는 로지스틱 회귀를 이용하여 문단의 카테고리를 분류하여 본문의 카테고리 분포도를 계산하고 Word2Vec을 이용하여 문단간의 유사도를 계산한 결과에 가중치를 부여하여 부적합 문단을 검출한다.

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Detecting Improper Sentences in a News Article Using Text Mining (텍스트 마이닝을 이용한 기사 내 부적합 문단 검출 시스템)

  • Kim, Kyu-Wan;Sin, Hyun-Ju;Kim, Seon-Jin;Lee, Hyun Ah
    • 한국어정보학회:학술대회논문집
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    • 2017.10a
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    • pp.294-297
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    • 2017
  • SNS와 스마트기기의 발전으로 온라인을 통한 뉴스 배포가 용이해지면서 악의적으로 조작된 뉴스가 급속도로 생성되어 확산되고 있다. 뉴스 조작은 다양한 형태로 이루어지는데, 이 중에서 정상적인 기사 내에 광고나 낚시성 내용을 포함시켜 독자가 의도하지 않은 정보에 노출되게 하는 형태는 독자가 해당 내용을 진짜 뉴스로 받아들이기 쉽다. 본 논문에서는 뉴스 기사 내에 포함된 문단 중에서 부적합한 문단이 포함 되었는지를 판정하기 위한 방법을 제안한다. 제안하는 방식에서는 자연어 처리에 유용한 Convolutional Neural Network(CNN)모델 중 Word2Vec과 tf-idf 알고리즘, 로지스틱 회귀를 함께 이용하여 뉴스 부적합 문단을 검출한다. 본 시스템에서는 로지스틱 회귀를 이용하여 문단의 카테고리를 분류하여 본문의 카테고리 분포도를 계산하고 Word2Vec을 이용하여 문단간의 유사도를 계산한 결과에 가중치를 부여하여 부적합 문단을 검출한다.

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The Daily Us (vs. Them) from Online to Offline: Japan's Media Manipulation and Cultural Transcoding of Collective Memories

  • Ogasawara, Midori
    • Journal of Contemporary Eastern Asia
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    • v.18 no.2
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    • pp.49-67
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    • 2019
  • Since returning to power in 2012, the second Abe administration has pressured Japanese mainstream media in various ways, from creating the Secrecy Act to forming close relationships with media executives and promoting anti-journalism voices on social media. This article focuses on the growth of a jingoist group called the 'Net-rightists' ('Neto-uyo' in the Japanese abbreviation) on the Internet, which has been supporting the right-wing government and amplifying its historical revisionist views of Japanese colonialism. These heavy Internet users deny Japan's war crimes against neighboring Asian countries and disseminate fake news about the past, which justifies Prime Minister Shinzo Abe's hostile diplomatic policies against South Korea and China. Over the past years, the rightist online discourses have become powerful to such an extent that the editorials of major newspapers and TV reports shifted to more nationalist tones. Who are the Neto-uyo? Why have they emerged from the online world and proliferated to the offline world? Two significant characteristics of new media are discussed to analyze their successful media manipulation: cultural transcoding and perpetual rewriting of collective memories. These characteristics have resulted in constructing and reinforcing the data loops of the 'Daily Us' versus Them, technologically raising current diplomatic tensions in East Asia.

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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A study on the accuracy of environmental reporting in korean nine dailies (국내 중앙 일간지 환경보도의 정확성에 관한 연구)

  • 안종주
    • Proceedings of the Korean Environmental Health Society Conference
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    • 2002.04a
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    • pp.52-54
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    • 2002
  • Generally, inaccurate reports on environmental issues occur due to various factors. The purpose of this study was to find out a way to enhance accuracy of environmental reporting. So the reporters' career and college major had been compared to the accuracy of their articles. The by-lined environmental articles in nine dailies published in 1991 were checked. Results of this study were as follows. (1) Inaccuracy rate in environmental articles was 54.2%. Inaccuracies appeared 1.7 times per an article, while the average frequency of inaccuracies in overall articles was 0.9 time. (2) Errors in the articles consist of 65.8% of subjective inaccuracies and 34.2% of subjective inaccuracies. They derive from the false usage of terminology(15.8%), misquotation(14.5%), incorrect statistics(13%), exaggeration(13%), inaccurate title(7.9%), and false comparison(5%), (3) Inaccuracy rate by the type of articles was 66.7% in columns, 60% in feature stories, 54.5% in-depth stories, 40.9% in straight news, respectively. (4) Inaccuracy rate by the specific field was shown 71.4% in environmental impacts (5) According to the result of chi-square test analysis, there were no statistically significant differences of inaccuracy rate and of subjective, and objective, and objective inaccuracies relevant to the period of reporters' career covering environmental reporting and the nature of articles, and college major.

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