• The Journal of Society for e-Business Studies
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• v.14 no.2
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• pp.41-56
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• 2009

The purpose of this paper is to present a statistical model that can predict the rapid shift of users' attention by analyzing the lifecycle patterns of news in a social news aggregation service. Internet news service sites have a distinct characteristic in a sense that users' attention change very quickly in a short period of time. In this research, we propose a regression model for each news category which can model the decay pattern of users' attention and the content promotion policy of a social news aggregator is proven to be a major source of the rapid growth in the popularity of news. The proposed model is expected to be useful for evaluation of the social news aggregation service provider's content promotion policy that attempts to maximize users' attention as well as the diversity of news contents.

• Informatization Policy
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• v.19 no.3
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• pp.19-35
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• 2012

As Internet users increasingly consume news through the Internet, Internet portals face criticism that they are quickening the softening of public news and molding public opinions. Some portals have started to provide newscast services that directly connect the press, not grouping news sources on their own standards. This study aims to clarify how news grouping models and newscast models are different in terms of news softening and agenda setting. Specifically, authors conduct a content analysis on time-specific news content provided by top three portals-Naver, Daum, and Nate. By doing so, this study examines characteristics of news service models of Internet portals and their social and political implications. According to our study, the softening and tabloidization of portal news had not been improved even after adopting the newscast model. Therefore, portal journalism should be reorganized as a way to circulate healthy and qualified news content.

• 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.

• 중국학논총
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• no.66
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• pp.45-61
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• 2020

Chinese for Journalism and Communication (CJC) is used not only to communicate, gather, read and understand the news and information in the daily life, but also to work as a professional in journalism. It includes daily CJC and professional CJC. It has similarities and difference with journalism terms. The lexical values of CJC words includes: recognition value, frequency value, composition value, and aggregation value.

• The Korean Journal of Blood Transfusion
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• v.29 no.3
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• pp.229-239
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• 2018

The circulatory system is closely related to the inter-relationship between the anatomy of the heart and blood vessels, and the fluid dynamic properties of blood. The physical properties of blood, which affect blood flow, are called hemorheologic factors. Hemorheologic factors, such as blood viscosity and erythrocyte aggregation, are influenced mainly by hematocrit. A higher hematocrit level results in an increase in blood viscosity, erythrocyte aggregation, which impedes the circulation itself, and tissue oxygenation. An excess of serum ferritin causes injury to vascular endothelial cells and erythrocytes via oxygen free radicals. In addition, an excess of blood can aggravatee the adverse effects of the hemorheologic parameters and induce atherogenesis, microcirculatory disturbances, and major cardiovascular events. A preventive and therapeutic approach with a phlebotomy or blood donation has been stimulated by the knowledge that blood loss, such as regular donations, is associated with significant decreases in key hemorheologic variables, including blood viscosity, erythrocyte aggregation, hematocrit, and fibrinogen. Major cardiovascular events have been improved in regular blood donors by improving blood flow and microcirculation by decreasing the level of oxidative stress, improving the hemorheologic parameters, and reducing the serum ferritin level. Confirmation of the positive preventive and therapeutic effects of blood donations on cardiovascular disease by a well-designed and well-controlled Cohort study may be good news to patients with cardiovascular disease or at risk of these diseases, as well as patients who require a transfusion.

• Journal of Computing Science and Engineering
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• v.11 no.2
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• pp.39-48
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• 2017

Main content extraction of web pages is widely used in search engines, web content aggregation and mobile Internet browsing. However, a mass of irrelevant information such as advertisement, irrelevant navigation and trash information is included in web pages. Such irrelevant information reduces the efficiency of web content processing in content-based applications. The purpose of this paper is to propose an automatic main content extraction method of web pages. In this method, we use two indicators to describe characteristics of web pages: text density and hyperlink density. According to continuous distribution of similar content on a page, we use an estimation algorithm to judge if a node is a content node or a noisy node based on characteristics of the node and neighboring nodes. This algorithm enables us to filter advertisement nodes and irrelevant navigation. Experimental results on 10 news websites revealed that our algorithm could achieve a 96.34% average acceptable rate.