• International Journal of Advanced Culture Technology
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• v.6 no.2
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• pp.65-71
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• 2018

In the digital era, news consumption is not confined in geological boundaries. Technological advances bring the instant dissemination of news into life and allow news audience to consume events that occur far away almost in real time. The transmission has blurred the boundary between traditional media and new media, and the one between physical and virtual world. That is, what if a journalist applies news framing to the news translation process? This paper aims to investigate the gap between the ST and the TT created when the source news texts undergo a translation process. To achieve this aim, the appraisal theory developed by White (2003) is employed to identify a difference between the ST and the TT. Furthermore, we have attempted to identify differences between soft news stories and hard news stories while the STs from both news stories are translated into the TTs. Two time-sensitive events, Hugh Grant's marriage and a U.S. and North Korea summit, were selected. The former (a soft news story) is extracted from the Telegraph and the latter (a hard news story) is from the Washington post. As a result, it was found that such strategies as attitude, engagement, and judgment were used when the source news texts from the hard news story are translated into the target news texts. Under the appraisal theory, the strategies involve evaluative language which refers to positive or negative language that judges the worth of entities. In general, it is said that a journalist frames the SS (especially from the hard news story) to convey his ideology to news consumers. Hypothetically, we assume that a similar framing process takes place in deriving the TT from the SS of the hard news story. Thus, we could conclude that the TT from the hard news story differs from the TT from the soft news story and that the difference can be explained within the framework of White's appraisal theory.

• International Journal of Contents
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• v.13 no.1
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• pp.1-8
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• 2017

The study aims to reveal the differences in the factors influencing portal news and news site application usages on smartphones in regard to political discussion networks, news use across multiple media platforms and news genre consumption. The results demonstrate that those factors affected both types of application usages in a different manner when controlling for demographics. The more participants conversed politics with homogeneous networks, the more they used portal news on smartphones. Conversely, the more political discussion with heterogeneous networks, the more they used news site application on smartphones. The more frequently Internet and mobile phone were employed for news source and the more soft news genre was consumed, the more the portal news application was used. However, the more frequently traditional and social media were employed for news source and the more hard news consumed, the more news site application was used. The findings imply that portal news application users may increase their likelihood of soft news consumption using Internet and mobile phones for political discussion with close social relations, while news site application users may increase their likelihood of hard news consumption using traditional and social media for political discussion with distant social relations.

• Korean journal of communication and information
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• v.61
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• pp.74-97
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• 2013

Asia is developing rapidly in 21st century. Human and material exchanges between Korea and Asian countries have greatly increased. Korea entered the multicultural society. It became important for Korean people to understand Asia more correctively. Korean media can play a key role for this. In this point, I analyzed 1786 news contents reported in 2011 by four Korean newspapers(Chosun Ilbo, Dong-A Ilbo, Hankyoreh newspaper, Kyungh Kyunghyang Daily News), to see differences of Asia and West news aspect and its reason, focusing on news topic, amount of news, news tone and foreign media sources. In amount of news, the percent of West(54.3%) was higher than that of Asia news(45.7%). In news tone, negative news were the most in Asia news, but the least in West news. Korean newspaper showed more positive attitude to West than Asia. 1786 news were classified into seven topics(morality and justice, politics, economics and science, society, diplomacy and national defense, human interest, people). In news amount of seven topics, Korean newspapers reported hard news like morality and justice more than soft news like human interest about Asia. However they reported many soft news about West besides hard news. In news topics and tone, hard news showed negative tone most and soft news showed neutral or positive tone most. As a result, Korean news showed the negative attitude to Asia and the positive to West. Among five main sources(media, government, private organization, individual and material), only media source affected the differences of news attitude to Asia and West. Asia media source took the more positive attitude to Asia than West. West media took the negative attitude to Asia most and the neutral attitude to West most. Korean newspapers used West media as main sources in the news of all areas except East Asia. As a result, Korean newspapers showed the West-centered-attitude and reported the negative news more than neutral and positive about Asia. It was suggested that Korean newspapers had better increase Asia news in diverse spheres by the direct reporting of the correspondent and the more use of Asia media through the internet.

• International Journal of Contents
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• v.17 no.2
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• pp.48-64
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• 2021

This study examines mobile news engagement-conceptualized as news exposure and participation-in the context of South Asia which has experienced tremendous growth in mobile-Internet users without receiving much attention from communication scholars. Along with demographic characteristics, this research incorporates motivational factors (grounded on uses and gratifications-U&G-approach) and news type preferences to explore their roles in mobile news engagement among urban citizens in Bangladesh. Results of a self-administered survey (N = 504) revealed that participants' mobile news engagement partially varied depending on their demographic differences, particularly gender, age, and education. Our study also unveiled that individuals' motivation for sharing information seemed to be a strong predictor of mobile news exposure and participation. In addition, Bangladeshi respondents were more likely to be interested in the hard news in terms of expressing views on news comments and sharing news via mobile platform. Conversely, preference for soft type news had a significant influence on news exposure through mobile browsing. This study provides insights into the understanding of global phenomena of mobile news engagement by unpacking the case of Bangladesh where mobile news usage seems to be an evolving state.

• Journal of Internet Computing and Services
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• v.19 no.2
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• pp.49-56
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• 2018

Internet news consumption is rapidly growing in Korea, and majority of that is being done through Naver, Korea's primary search engine. Naver is also the go-to search engine for smartphone use. This study analyzed 824 most popular news accessed via mobile gears; the news items were selected from Naver's 'Daily Top 10 Stories,' dating from March 2016 to December 2016. The results indicate that entertainment news were the most viewed, while political and social issue news were the most liked and commented by mobile users. With regard to news value, 'prominence' and 'impact' were the two most important factors that influenced a user's news selection process in a mobile environment. The degree of a news' 'prominence' was the most important factor that determined the number of views, while 'impact' was critical to determining "the most commented-upon" and "the most liked" news. The results also indicate that mobile news consumers prefer more dramatic storylines and events that incite public anger or grief, threaten the safety of citizens, or evoke emotional sympathy rather than 'hard news' about such subjects as politics and economics.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.219-234
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• 2019

Fake news threaten democratic elections and causes social conflicts, resulting in major damage. However, the concept of fake news is hard to define, as there is a saying, "News is not fake, fake is not news." Fake news, however, has irreversible characteristics that can not be recovered or reversed completely through post-punishment of economic and political benefits. It is also rapidly spreading in the early days. Therefore, it is very important to preemptively detect these types of articles and prevent their blind proliferation. The existing countermeasures are focused on reporting fake news, raising the level of punishment, and the media & academia to determine the authenticity of the news. Researchers are also trying to determine the authenticity by analyzing its contents. Apart from the contents of fake news, determining the behavioral characteristics of the promoters and its qualities can help identify the possibility of having fake news in advance. The online community has a fake news interception and response tradition through its long-standing community-based activities. As a result, I attempted to model the fake news by analyzing the affirmation-denial analysis and posting behavior by securing the web board crawl of the 'M community' bulletin board during the 2017 Korean presidential election period. Random forest algorithm deemed significant. The results of this research will help counteract fake news and focus on preemptive blocking through behavioral analysis rather than post-judgment after semantic analysis.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.612-617
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• 2008

To develop the broadcasting application for DMB, the programmers have to aggregate the content. In this case of content such as news, it would be hard to provide successively updated content. This paper introduces a creation system which can automatically create the news application for data broadcasting on DMB based on the web news content updated immediately. The designed creation system aggregates the news content using RSS based XML and produces the news application by transcoding the web content which can be applied on DMB.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.23-28
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• 2022

Recently smart device(such as smart phone and tablet PC) become a role as an information gateway, using of the web news by multiple users from the web portal has been more important things. However, the quantity of creating web news on the web makes hard to catch the information which the user wants and confuse the users cause of the similar and repeated contents. In this paper, we propose the news recommend system using the document summarization based on KoBART which gives the selected news to users from the candidate news on the news portal. As a result, our proposed system shows higher performance and recommending the news efficiently by pre-training and fine-tuning the KoBART using collected news data.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.10-22
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• 2021

This study conducted usability test to users in 20s in order to find problems for improving news apps of the major broadcasting companies. Efficiency, effectiveness, and satisfaction were evaluated by mobile news content type. Also there is including analysis of the news topics (hard news, soft news) and broadcasters (MBC, SBS). As a result, same problems were found in common items according to mobile news content types. And in the news topic, there was a difference in the news values and news attributes that need to be improved. This study gives practical implications to the news producers to improve the contents of news apps.

• 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%.