• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.726-734
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• 2019

This study investigates the number of news and correlated keywords concerning to Korean Wireless Emergency Alert(KWEA). The news was collected using BIGKinds, a news big data system provided by the Korea Press Foundation. When analyzing the annual published news articles, we investigated the frequency of the news grouped by disaster types, and the frequency of the news distinguishing between the earthquake and non-earthquake disasters, and finally the frequency of correlated keywords concerning to the disasters. We found that the KWEA news totaled 182 in 2016 due to the unprecedented powerful KyongJu earthquake, an increase of 20 times over the previous year. Ever since 2016, the news about the KWEA continued to hit high figures consistently. After the peak in KyongJu earthquake in 2016, the proportion of non-earthquakes had also increased in 2017 and 2018. Next, the keyword correlation analysis showed that the KWEA news gave major coverage to the following entities: The Ministry of the Interior and Safety which operates the KWEA, Korea Meteorological Administration, and the general public.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.141-148
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• 2019

In this study, the Technology Acceptance Model (TAM) was applied to explore the process of using card news. Card news users are found to be active in searching and selecting appropriate news for themselves, information seeking style and news literacy were established as antecedent variables that can influence card news usage. A survey of 400 university students with experience of using card news was conducted. For statistical analysis, SEM was conducted. The analysis showed that information seeking style significantly affects perceived ease of use (PEU) and that news literacy influences neither PEU nor PU. PEU was found to have a significant effect on PU, and both PEU and PU had a significant effect on recommendation intention.

• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.40-53
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• 2019

Although fake news has been present in human history at any time, nowadays, with social media, deceptive information has a stronger effect on society than before. This article answers two research questions, namely (1) Is the dissemination of fake news supported by machines through the automatic construction of filter bubbles, and (2) Are echo chambers of fake news manmade, and if yes, what are the information behavior patterns of those individuals reacting to fake news? We discuss the role of filter bubbles by analyzing social media's ranking and results' presentation algorithms. To understand the roles of individuals in the process of making and cultivating echo chambers, we empirically study the effects of fake news on the information behavior of the audience, while working with a case study, applying quantitative and qualitative content analysis of online comments and replies (on a blog and on Reddit). Indeed, we found hints on filter bubbles; however, they are fed by the users' information behavior and only amplify users' behavioral patterns. Reading fake news and eventually drafting a comment or a reply may be the result of users' selective exposure to information leading to a confirmation bias; i.e. users prefer news (including fake news) fitting their pre-existing opinions. However, it is not possible to explain all information behavior patterns following fake news with the theory of selective exposure, but with a variety of further individual cognitive structures, such as non-argumentative or off-topic behavior, denial, moral outrage, meta-comments, insults, satire, and creation of a new rumor.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.628-644
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• 2021

The main purpose of this study is to search for variables that influence the perception of news of YouTube current affairs and political channel users. Existing studies have focused on providing normative criticism by examining the public opinion influence of YouTube channels, which play a role similar to the media, in terms of political polarization, fake news, and confirmation bias. However, this study attempts to examine the changes and meanings of users' perception of news with the advent of YouTube. To this end, an online survey was conducted for users with experience in using YouTube's current affairs and political channels. As a result of the study, it was found that the news perception of YouTube current affairs and political channel users was mixed with the perception of news from the perspective of professional journalism and the perception of newly added news in the digital environment. Based on these results, the researcher examined the implications of the professional news media's response direction to the platform environment.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• MALSORI
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• no.50
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• pp.71-83
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• 2004

Recently, broadcast news speech recognition has become one of the most attractive research areas. If we can transcribe automatically the broadcast news and store their contents in the text form instead of the video or audio signal itself, it will be much easier for us to search for the multimedia databases to obtain what we need. However, the desirable speech signal in the broadcast news are usually affected by the interfering signals such as the background noise and/or the music. Also, the speech of the reporter who is speaking over the telephone or with the ill-conditioned microphone is severely distorted by the channel effect. The interfered or distorted speech may be the main reason for the poor performance in the broadcast news speech recognition. In this paper, we investigated some methods to cope with the problems and we could see some performance improvements in the noisy broadcast news speech recognition.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.619-622
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• 2008

뉴스 분류 체계는 각각의 기사에 정치, 경제, 사회 등 가장 적합한 주제별로 분류하는 것으로 언론사별 분류 체계는 통일성이 없이 전혀 다르게 구성되어 사용하고 있다. 이로 인해 방대한 콘텐트를 통합하는데 많은 어려움이 있으며, 그만큼 시스템과 인력에 대해 중복 투자가 되고 있다. 이런 문제점을 개선하기 위해 국제 표준인 NewsML에 기반한 뉴스 분류에 대해 제안한다. NewsML은 XML 기반의 유연성과 확장성이 있는 구조적인 표준 형식으로 다양한 데이터 표현이 가능하여 자동 문서 범주화에 필요한 중요한 자질 선택이 가능하다. 본 논문에서는 NewsML 형식으로 되어 있는 뉴스와 그렇지 않은 뉴스를 구분하여 자동 분류에 대한 비교 실험을 한다. NewsML의 구조화된 정보를 활용한 실험이 뉴스의 제목과 본문만으로 실험한 결과보다 좋은 성능을 보여 주었으며, 그 중에서 자질 공간이 아주 큰 경우에 유용하고 문서 분류에 효과가 뛰어난 지지 벡터 기계 모델이 가장 좋은 성능을 보였다.

• Information Systems Review
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• v.23 no.4
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• pp.147-163
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• 2021

We investigate the effect of comment history disclosure on portal news comments. Specifically, based on the scraped news comments from Naver and Daum (two leading Korean news portals), we employ the difference-in-differences estimator to empirically tease out the impact of the comment history disclosure policy implemented in Naver on its news comments. Our result shows that the policy implementation significantly increased the length and the positiveness of online news comments but did not affect their quality.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.293-311
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• 2020

Recently, it is more important to study the reasons for using media than which media is selected. This paper investigates different countries as objects to conduct the survey. In accordance with the research results, in hypothesis 1, there is a positive "(+)" influence of its interestingness, informality, restlessness, news pursuit and convenience on satisfaction when college students in South Korea use net news. Taking Chinese college students as an example, there is a positive "(+)" influence of the using motivation of net news on news pursuit, habituation, interactivity, convenience and the satisfaction with net news. In hypothesis 2, the interestingness, informality, habituation and convenience of the using motivation of online news of college students in South Korea are reflected in the acceptance intention of online news, while for Chinese college students, the informality, habituation and convenience are reflected in the acceptance intention of online news. Finally, in hypothesis 3, there is a positive "(+)" influence of the satisfaction of online news on the acceptance level of online news. In addition, this research also considers that the PLS path coefficient of college students in South Korea and China is different, and the motivations and purposes for using net news by two countries are different due to the characteristics and cultures of news media in different countries, so the satisfaction is also different.

• Korean journal of communication and information
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• v.56
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• pp.48-70
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• 2011

Although many researchers propose that market-driven journalism is incurred by the worsening of financial situation as a result of intensifying competition in mass media industry, few studies investigated this claim with actual news data. This study analyzed the headline news of eight major newspapers and two terrestrial TV companies to find the weakening of 'orientating-journalism' function of Korean news media. The results revealed that the duplication rate of news items among ten news companies were decreasing, and the range of news subjects were broadened into diverse topics during last ten years. Therefore it seemed that the tendency of monopolization of a certain events or issues was weakening in news reporting. The financial situation of news companies is an important factor in explaining the change of news reporting. The companies with more worse financial situation have higher duplication rate of news topics along as the more amount of soft news items, leading to the gradual deterioration of their own voices in reporting. The rate of 'independent issue report' was also less than seven precent, thus their reporting is evaluated as having many limitations. In sum, the major newspapers and network broadcasting companies are still exerting strong influences in agenda-setting, but they(mostly newspapers) are suffering from the financial problems, resulting the deterioration of performing orientation journalism function. This study concluded with remarks about the role of major news media in current changing situation.