• The Journal of Korean Academic Society of Nursing Education
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• v.24 no.4
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• pp.453-462
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• 2018

Purpose: This study analyzed how the four nurse-related news items 'talent show,' 'neonatal death,' 'nurse's death,' and 'sexual harassment' were portrayed in Korean daily newspaper articles. Methods: A total of 392 newspaper articles published from November 2017 to May 2018 were retrieved through the internet homepages of three newspapers, the Chosun Ilbo, the Dong-a Ilbo, and the JoongAng Ilbo and through a database for 13 other newspapers. Articles were analyzed for their views on nurses and their structural and contextual frames. Results: Articles with the highest frequency of mentioning nurses' death appeared in the JoongAng Ilbo; these were written as straight news articles. In the analyzed articles, nurses were portrayed mostly as victims, troublemakers, passive, or selfish. Articles were written mostly in episodic, incident notice, or attribution of responsibility frames. Conclusion: It was not uncommon to read articles with negative views on nurses; most of these articles focused only the four major incidents as straight news type stories. Future efforts are needed to study the implications of newspaper articles with negative views on nurses and the frames most commonly used.

• Korean journal of communication and information
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• v.39
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• pp.324-354
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• 2007

Facts, which constitute news, are as free as air. When they are transformed into news via labor and capital investment of a news organization, the news is deemed to have property values, and the media can claim exclusive rights over the news. The copyright law protects the originality of a work, the uniqueness of reporter's analysis, the selection of words, the arrangement of materials, and the emphasis given on particular points. The name of the game of copyright infringement lies in the infringement of the similarity of the method of expression, not the infringement of the subject. Even though news articles convey information by specifying factual elements of an event or accident, they still have some originality. The judgement that news articles lack of originality is inconsistent with the purpose of the copyright law. Therefore, the law should be amended to articulate that the unauthorized use of news articles without a proper citation shall be the subject of legal action, and courts should decide related cases accordingly.

• Journal of Society of Preventive Korean Medicine
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• v.27 no.3
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• pp.1-12
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• 2023

Objectives : The aim of this study is to analyze the news articles related to Korean Medicine(KM) and compare trends in news reports from 2018 to 2022. Method : News articles related to KM were collected through the BigKinds, the news bigdata service of the Korea Press Foundation. News reports from 1 January 2018 to 31 December 2022 were searched. 2,950 news articles out of a total of 12,497 met the inclusion criteria. First, quantitative changes in media coverage were analyzed by year, media outlet, and month. For qualitative analysis, two authors independently coded the content of news articles, discussed them until consensus, and consulted with a third researcher to classify them. In addition, keywords extracted by the BigKind's Topic Rank algorithm were compared and analyzed in each year. Results : The number of news articles on KM decreased by 42% in 2022 compared to 2018. Over a fiveyear period, the Naeil Shinmun reported the most on KM among newspapers, while the Hankyoreh did the least. Among broadcasters, YTN reported the most and SBS did the least. When analyzing the reports by category, the most common was 'treatment', followed by 'prevention' and 'scientification'. As a result of extracting keywords with high weight and frequency, 'immunity' and 'immune system' ranked the first and second in 2018, while 'COVID 19' and 'medical law violation' did in 2022. Conclusion : The decrease in media reports on KM during the COVID-19 epidemic period seems to be due to the limited role of KM in responding to infectious diseases, and efforts to expand the scope of KM can induce increased media reports and social interest.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1313-1323
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• 2019

With the development of the Internet and the increase of smart phones, various services considering user convenience are increasing, so that users can check news in real time anytime and anywhere. However, online news is categorized by media and category, and it provides only a few related search terms, making it difficult to find related news related to keywords. In order to solve this problem, we propose a method to recommend related documents more accurately by applying Doc2Vec similarity to the specific keywords of news articles and weighting the title and contents of news articles. We collect news articles from Naver politics category by web crawling in Java environment, preprocess them, extract topics using LDA modeling, and find similarities using Doc2Vec. To supplement Doc2Vec, we apply TF-IDF to obtain TC(Title Contents) weights for the title and contents of news articles. Then we combine Doc2Vec similarity and TC weight to generate TC weight-similarity and evaluate the similarity between words using PMI technique to confirm the keyword association.

• Korean journal of communication and information
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• v.42
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• pp.140-167
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• 2008

This study analyzes the legal reasoning of Seoul Central District Court, which imposed legal liability on portals for posting defamatory user replies to news articles, written and provided by the news media, onto their 'News Windows'. Saddling portals with the burden of verifying the facts associated in news articles and imposing the legal obligation as a publisher entail a grave risk of impairment of free flow of information and freedom of expression. Of course, it would ultimately result in tightening up private censorship of information which the Constitution does not allow, and funker keep portals from posting even news articles in which expressed views and opinions are lawful. When judging whether portals should assume liability fur libelous user replies to news articles, it is necessary to distinguish the territory under the direct authority of portals from cafes and bulletin boards managed by third parties. In addition, imposing legal liability above the level of common carrier should be limited to the cases; when portals arbitrarily change the contents of news articles or when the articles portals changed contain libelous contents. Even if those conditions are met, the altered contents should obviously constitute libel. Only in the presence of proof that portals knew the illegality of news articles and did not take proper steps including deleting those replies, should portals not be considered as an accomplice. Nor should portals take responsibility for users' defamatory replies for those reasons.

• MALSORI
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• no.51
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• pp.99-115
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• 2004

In this parer, we propose LM adaptation for broadcast news recognition. We collect information of recent articles from the internet on real time, make a recent small size LM, and then interpolate recent LM with a existing LM composed of existing large broadcast news corpus. We performed interpolation experiments to get the best type of articles from recent corpus because collected recent corpus is composed of articles which are related with test set, and which are unrelated. When we made an adapted LM using recent LM with similar articles to test set through Tf-Idf method and existing LM, we got the best result that ERR of pseudo-morpheme based recognition performance has 17.2 % improvement and the number of OOV has reduction from 70 to 27.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.999-1005
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• 2020

While search portals' 'Portal News' account for the largest portion of aggregated news outlet, its neutrality as an outlet is questionable. This is because news aggregation may lead to prejudiced information consumption by recommending biased news articles. In this paper we introduce a new method of measuring political bias of news articles by using deep learning. It can provide its readers with insights on critical thinking. For this method, we build the dataset for deep learning by analyzing articles' bias from keywords, sourced from the National Assembly proceedings, and assigning bias to said keywords. Based on these data, news article bias is calculated by applying deep learning with a combination of Convolution Neural Network and Recurrent Neural Network. Using this method, 95.6% of sentences are correctly distinguished as either conservative or progressive-biased; on the entire article, the accuracy is 46.0%. This enables analyzing any articles' bias between conservative and progressive unlike previous methods that were limited on article subjects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.811-819
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• 2023

Understanding the local conditions is a crucial factor in enhancing the success potential of overseas construction projects. This can be achieved through the analysis of news articles of the target market using topic modeling techniques. In this study, the authors aimed to analyze news articles using two topic modeling methods, namely Latent Dirichlet Allocation (LDA) and BERTopic, in order to determine the optimal approach for market condition analysis. To evaluate the alignment between the generated topics and the actual themes of the news documents, the research collected 6,273 BBC news articles, created ground truth data for individual news article topics, and finally compared this ground truth with the results of the topic modeling. The F1 score for LDA was 0.011, while BERTopic achieved a score of 0.244. These results indicate that BERTopic more accurately reflected the actual topics of news articles, making it more effective for understanding the overseas construction market.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.631-637
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• 2018

In order to read newspaper articles, the use of paper newspapers is decreasing and smartphone are increasingly used. As a result, the number of news apps continues to increase. Many of the news apps in the Android Play Store fall into two categories. The first is an app that is developed by a specific newspaper company and distributes only the articles of the newspaper company. The rest is an app that shows a list of newspapers and shows the homepage when a newspaper is selected. In this paper, we have designed and implemented a Real-Time News app for collecting articles from many newspapers and providing them in real time. Newspapers provide up-to-date articles with RSS feeds. The server program stores them in the DB, and transmits the articles requested in the Real-Time News app in real time. In order to see the latest news, it is possible to collect the articles of each newspaper without visiting the websites of the various newspapers, and it is possible to reduce the mobile data usage used to access each website.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.159-178
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• 2019

The purpose of the study is to examine the trend in the change of relation between countries (Czech and Korea) through analysis of portal new articles. In order to achieve the purpose, we analyzed news articles about Czech from 1990 to March 31st, 2019. We divided it into 6 periods by every 5 years, reviewed 200 news articles for each period totaling 1,200 news articles, and categorized them into 4 categories by subject (politics, economy, society and culture, and educations). The result of the study showed the subject of society and culture represented the largest proportion of all news articles. We also found that the range of changes in the sub-categories of society and culture occurred most extensively. We concluded the paper with several suggestions that could promote cooperation between Korea and Czech.