• Journal of the Korean Society for information Management
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• v.26 no.1
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• pp.305-320
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• 2009

The news pages provided through the web contain unnecessary information. This causes low performance and inefficiency of the news processing system. In this study, news content extraction methods, which are based on sentence identification and block-level tags news web pages, was suggested. To obtain optimal performance, combinations of these methods were applied. The results showed good performance when using an extraction method which applied the sentence identification and eliminated hyperlink text from web pages. Moreover, this method showed better results when combined with the extraction method which used block-level. Extraction methods, which used sentence identification, were effective for raising the extraction recall ratio.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.123-141
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• 2007

It has been known that predicting stock price is very difficult due to a large number of known and unknown factors and their interactions, which could influence the stock price. However, we started with a simple assumption that good news about a particular company will likely to influence its stock price to go up and vice versa. This assumption was verified to be correct by manually analyzing how the stock prices change after the relevant news stories were released. This means that we will be able to predict the stock price change to a certain degree if there is a reliable method to classify news stories as either favorable or unfavorable toward the company mentioned in the news. To classify a large number of news stories consistently and rapidly, we developed and evaluated a natural language processing based multi-stage news classification system, which categorizes news stories into either good or bad. The evaluation result was promising as the automatic classification led to better than chance prediction of the stock price change.

• Land and Housing Review
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• v.12 no.3
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• pp.27-37
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• 2021

This paper empirically examined the relationship between the housing market and the stock market to investigate the price and the asymmetric volatility spillover effects. The monthly housing price index and the monthly KOSPI were used for analysis. This research employed the EGARCH model. The analysis period was from January 1986 until June 2021 with periodization centered on the Asian Financial Crisis: before and after the crisis - the end of December 1997. The EGARCH model allows analysis of 'good news' and 'bad news' in understanding volatility. The price spillover effect was observed one way from the stock market to the housing market. On the contrary, the spillover effect was not found from the housing market to the stock market. The empirical evidence suggests that there are price and asymmetric volatility effects in the entire period of analysis in both housing and the stock markets. In the housing market, the negative effects of information were found pre-financial crisis while the positive effects, in other periods. However, in the stock market, the negative effects of information were found in the pre- and post-financial crisis periods. This means that the housing market is more affected by 'good news' than 'bad news' when information spreads to the markets while the stock market is more affected by 'bad news' than 'good news'. It is of significance to discover the variable returns by different information.

• Journal of Korean Home Economics Education Association
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• v.10 no.1
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• pp.1-16
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• 1998

The purpose of this study was to investigate the middle school and high school student's environmental consciousness and clothing behavior for environmental protection in their home, and to present the basic educational material for the reasonable clothing behavior which could help the environmental problems. This study was done by self-administered questionaires to the 439 middle school and high school students, and done from March to April in 1997. Frequencies, percentages, mean, and standard deviation were calculated. $\chi$$^2$-test, t-test, and F-test were done for group differences, and Duncan's multiple range test was followed. The results of this study were as follows ; 1. Environmental consciousness was higher at the middle school students, at good graded students, and at the good news receivers who watch or listen to the mass media frequently. And also environmental consciousness was higher at the students who separate and dispose waste practically and at those who realize the need of environmental education. 2. Those who purchase clothes reasonably in their home, practising the clothing behavior for environmental protection, were the middle school students, and the students sho watch or listen news frequently through the mass media. And those who manage clothes well in their home were the middle school students, metropolitan area residents, good news receivers, and residents in apartments. Those who separate and dispose waste well, those who have experienced much environmental education, those who know better the environmental protection marks which are attatched to the low pollution products and those who realize the need of environmental education seriously, were almost the same students who buy and manage clothes reasonably in their home, practising the clothing behavior for the environmental protection. And those who feel much more environmental education seriously were those who reuse clothes practically in their home. 3. As the students had the higher environmental consciousness level, the better they practised the clothing behavior for environmental protection in their home. The major sources of the students'knowledge and information about environment were from the mass medea, and then from school teachers.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.387-394
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• 2016

The volatility in the stock market responds differently to information types. That is, the asymmetric volatility exists in the stock market which responds more to unexpected negative returns due to bad news than unexpected positive returns due to good news. This paper examines the asymmetric response of the volatility of KOSPI, large-cap, middle-cap, and small-cap indices returns which is announced in Korea exchange (KRX) by using the MA-GJR model and the MA-EGARCH model. According to empirical analyses, it shows that the asymmetric response of volatility exists in all indices regardless of volatility estimation models and the degree of the asymmetric volatility response of the small-cap index returns is greater than that of the large-cap index returns. Moreover, this results also observed robustly during the period of both before and after the global financial crisis.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.175-194
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• 2004

Volumes of research have been implemented to estimate and predict the oil price. These models, however, fail in accurately predicting oil price as a model composed of only a few observable variables is limiting. Unobservable variables and news that have been overlooked in past research, yet have a high likelihood of affecting the oil price. Hence, this paper analyses the news impact on the price. The standard GARCH model fails in capturing some important features of the data. The estimated news impact curve for the GARCH model, which imposes symmetry on the conditional variances, suggests that the conditional variance is underestimated for negative shocks and overestimated for positive shocks. Hence, this paper introduces the asymmetric or leverage volatility models, in which good news and bad news have different impact on volatility. They include the EGARCH, AGARCH, and GJR models. The empirical results showed that negative shocks introduced more volatility than positive shocks. Overall, the AGARCH and GJR were the best at capturing this asymmetric effect. Furthermore, the GJR model successfully revealed the shape of the news impact curve and was a useful approach to modeling conditional heteroscedasticity.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.164-176
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• 2011

To get an implication for desirable direction for Collaboration between Reporter & Producer, I found that had 4 modes of collaboration such as, Producer System, Reporter System, Double Reporting System, Co-Work System, and each was distinguished by field cover, on-mic, editing, writing. Producer system and Reporter system got no chemical synergy because of simple array of single reports due to physical assemble. The achievements of collaboration was birth of new news which had different duration, visual, sound & perspective. It also offered fertile soil for new program and genre literacy of 8 o'clock news. The success factor of collaboration was surprisingly turned out to be personnel rather than system. The balance of reporter & producer was also good factor. But the wall between 2 groups was so high that, after disappearance of extraordinary leader, system began to crumble and at last program was repealed.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2749-2752
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• 2012

Background: Breaking bad news to cancer patients is a delicate and challenging task for most doctors. Better understanding of patients' preferences in breaking bad news can guide doctors in performing this task. Objectives: This study aimed to describe the preferences of Malaysian cancer patients regarding the communication of bad news. Methodology: This was a cross-sectional study conducted in the Oncology clinic of a tertiary teaching hospital. Two hundred adult cancer patients were recruited via purposive quota sampling. They were required to complete the Malay language version of the Measure of Patients' Preferences (MPP-BM) with minimal researcher assistance. Their responses were analysed using descriptive statistics. Association between demographic characteristics and domain scores were tested using non-parametric statistical tests. Results: Nine items were rated by the patients as essential: "Doctor is honest about the severity of my condition", "Doctor describing my treatment options in detail", "Doctor telling me best treatment options", Doctor letting me know all of the different treatment options", "Doctor being up to date on research on my type of cancer", "Doctor telling me news directly", "Being given detailed info about results of medical tests", "Being told in person", and "Having doctor offer hope about my condition". All these items had median scores of 5/5 (IQR:4-5). The median scores for the three domains were: "Content and Facilitation" 74/85, "Emotional Support" 23/30 and "Structural and Informational Support" 31/40. Ethnicity was found to be significantly associated with scores for "Content and Facilitation" and "Emotional Support". Educational status was significantly associated with scores for "Structural and Informational Support". Conclusion: Malaysian cancer patients appreciate the ability of the doctor to provide adequate information using good communication skills during the process of breaking bad news. Provision of emotional support, structural support and informational support were also highly appreciated.

• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.179-197
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• 2007

This paper analyzed the effects of interactions among participants on the satisfaction and commitment of cyber education. Even if the quality of interactions in cyber education may not be so good as that of interactions in face to face education. various kinds of interactions could be introduced in cyber education. An email or Q/A between lecturer and students could be a good way to compensate the deficiency of cyber education. Common News Boards or Discussion Rooms among students themselves are also a powerful means to learn each other in cyber space. The result of this study shows that as interactions among participants increase. satisfaction and commitment of the lecture also increase. This study also analyzed how cyber educational effects differs as interaction type changes in space dimension and time dimension. The result shows interactions in the same cyber space such as News Board brings more desirable outcome than those in the different cyber space. But the effects of interactions classified by time dimension does not show statistically significant differences.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.61-72
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• 2020

The fear of crime, discussed in the early 1960s in the United States, is a psychological response, such as anxiety or concern about crime, the potential victim of a crime. These anxiety factors lead to the burden of the individual in securing the psychological stability and indirect costs of the crime against the society. Fear of crime is not a good thing, and it is a part that needs to be adjusted so that it cannot be exaggerated and distorted by the policy together with the crime coping and resolution. This is because fear of crime has as much harm as damage caused by criminal act. Eric Pawson has argued that the popular impression of violent crime is not formed because of media reports, but by official statistics. Therefore, the police should watch and analyze news related to fear of crime to reduce the social cost of fear of crime and prepare a preemptive response policy before the people have 'fear of crime'. In this paper, we propose a deep - based news classification system that helps police cope with crimes related to crimes reported in the media efficiently and quickly and precisely. The goal is to establish a system that can quickly identify changes in security issues that are rapidly increasing by categorizing news related to crime among news articles. To construct the system, crime data was learned so that news could be classified according to the type of crime. Deep learning was applied by using Google tensor flow. In the future, it is necessary to continue research on the importance of keyword according to early detection of issues that are rapidly increasing by crime type and the power of the press, and it is also necessary to constantly supplement crime related corpus.